Diagnosis and treatment of autism spectrum disorder

ABSTRACT

Disclosed herein are compositions, systems, and methods for diagnosing and treatment of subjects suffering from anxiety, autism spectrum disorder (ASD), or a pathological condition with one or more of the symptoms of ASD.

RELATED APPLICATIONS

The present application claims priority under 35 U.S.C. §119(e) to U.S.Provisional Application No. 61/694,679, filed on Aug. 29, 2012, which isherein expressly incorporated by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED R&D

This invention was made with government support under grant no.W81XWH-11-0515 awarded by the Army, Graduate Training grant No. 5 T32GM07737 awarded by National Institutes of Health, Graduate ResearchFellowship No. DGE-0703267 awarded by National Science Foundation, andgrant No. MH100556 awarded by National Institutes of Mental Health. Thegovernment has certain rights in the invention.

REFERENCE TO SEQUENCE LISTING

The present application is being filed along with a Sequence Listing inelectronic format. The Sequence Listing is provided as a file entitledSEQLISTING.TXT, created Aug. 28, 2013, which is 4 Kb in size. Theinformation in the electronic format of the Sequence Listing isincorporated herein by reference in its entirety.

BACKGROUND

1. Field of the Invention

The present application relates generally to the field of diagnosing andtreatment of autism spectrum disorders (ASD).

2. Description of the Related Art

Autism spectrum disorder (ASD) is a serious neurodevelopmental disordercharacterized by stereotypic behaviors and deficits in language andsocial interaction. The reported incidence of autism has rapidlyincreased to 1 in 88 births in the United States as of 2008 (CDC, 2012),representing a significant medical and social burden in the comingdecades. Reproducible molecular diagnostics for ASD have not beendeveloped and therapies for treating the core symptoms of ASD arelimited, and reproducible molecular diagnostics have not been developed.Much research into autism spectrum disorder (ASD) has focused ongenetic, behavioral and neurological aspects of disease, but primaryroles for environmental risk factors (Hallmayer et al., 2011), immunedysregulation and additional peripheral disruptions in the pathogenesisof ASD have recently gained significant attention. The strikingheterogeneity among individuals that share the same diagnosis isconsistent with the prevailing notion that there are a variety ofetiologies for ASD. Moreover, the spectrum of ASD symptoms andchallenges in identifying specific causes, treatments and molecularbiomarkers underscore the need to better define the clinical subtypes ofASD and provide tailored treatment to subclasses of ASD individuals.

SUMMARY

Some embodiments disclosed herein are related to a method for improvingbehavioral performance in a subject, where the method includes:determining the blood level of an autism spectrum disorder (ASD)-relatedmetabolite in a subject in need of treatment; and adjusting the bloodlevel of the ASD-related metabolite in the subject until an improvementin the behavioral performance in the subject is observed.

In some embodiments, the subject suffers from anxiety, autism spectrumdisorder (ASD), or a pathological condition with one or more of thesymptoms of ASD. In some embodiments, the subject suffers from ASD.

In some embodiments, adjusting the blood level of the ASD-relatedmetabolite comprises adjusting the composition of gut microbiota in thesubject. In some embodiments, adjusting the composition of gutmicrobiota of the subject comprises fecal transplantation. In someembodiments, adjusting the composition of gut microbiota of the subjectcomprises administering the subject a composition comprising Bacteroidesbacteria. In some embodiments, the Bacteroides bacteria is B. fragilis,B. thetaiotaomicron, B. vulgatus, or a mixture thereof.

In some embodiments, the composition is a probiotic composition, aneutraceutical, a pharmaceutical composition, or a mixture thereof.

In some embodiments, adjusting the composition of gut microbiota of thesubject comprises reducing the level of Clostridia bacteria in thesubject. In some embodiments, the Clostridia bacteria isLachnospiraceae. In some embodiments, adjusting the composition of gutmicrobiota of the subject comprises increasing the level ofRuminococcaceae, Erysipelotrichaceae, and/or Alcaligenaceae bacteria inthe subject.

In some embodiments, the ASD-related metabolite is one of themetabolites listed in Table 1. In some embodiments, the ASD-relatedmetabolite is a metabolite involved in tryptophan metabolism, ametabolite involved in fatty acid metabolism, a metabolite involved inpurine metabolism, glycolate, imidazole propionate, or N-acetylserine.In some embodiments, the metabolite involved in tryptophan metabolism is4-ethylphenylsulfate, indolepyruvate, indolyl-3-acryloylglycine, orserotonin. In some embodiments, the ASD-related metabolite is4-ethylphenylsulfate, indolepyruvate, glycolate, or imidazoleproprionate.

In some embodiments, adjusting the blood level of the ASD-relatedmetabolite in the subject comprises administering to the subject anantibody against the ASD-related metabolite, an antibody against anintermediate for the in vivo synthesis of the ASD-related metabolite, oran antibody against a substrate for the in vivo synthesis of theASD-related metabolite.

In some embodiments, the ASD-related metabolite is 4-ethylphenylsulfateor indolepyruvate.

In some embodiments, adjusting the blood level of the ASD-relatedmetabolite in the subject comprises inhibiting an enzyme involved in thein vivo synthesis of the ASD-related metabolite.

In some embodiments, adjusting the blood level of the ASD-relatedmetabolite ameliorates gastrointestinal (GI) distress of the subject. Insome embodiments, the GI distress comprises abdominal cramps, chronicdiarrhea, constipation, intestinal permeability, or a combinationthereof. In some embodiments, adjusting the blood level of theASD-related metabolite reduces intestinal permeability of the subject.

In some embodiments, the method includes determining the reference levelof the metabolite in non-autistic subjects. In some embodiments, themethod includes determining the behavioral performance of the subjectprior to and after adjusting the blood level of the ASD-relatedmetabolite in the subject.

In some embodiments, determining the behavioral performance of thesubject comprises using Autism Behavior Checklist (ABC), Autismdiagnostic Interview-Revised (ADI-R), childhood autism Rating Scale(CARS), and/or Pre-Linguistic Autism Diagnostic Observation Schedule(PL-ADOS).

Also disclosed herein in some embodiments is a method for improvingbehavioral performance in a subject, where the method includes:determining the urine level of an autism spectrum disorder (ASD)-relatedmetabolite in a subject in need of treatment; and adjusting the urinelevel of the ASD-related metabolite in the subject until an improvementin behavioral performance in the subject is observed. In someembodiments, the ASD-related metabolite is 4-methylphenyl,4-methylphenylsulfate or indolyl-3-acryloylglycine.

In some embodiments, adjusting the urine level of the ASD-relatedmetabolite comprises adjusting the composition of gut microbiota in thesubject. In some embodiments, adjusting the composition of gutmicrobiota of the subject comprises administering the subject acomposition comprising Bacteroides bacteria.

Some embodiments provided here are related to a method for assessing thesusceptibility of a subject suffering from autism spectrum disorder(ASD) to probiotic treatment, where the method includes: determining theblood level of a B. fragilis-responsive metabolite in the subject; andcomparing the blood level of the B. fragilis-responsive metabolite inthe subject to a reference level of the metabolite in subjects sufferingfrom ASD and one or more gastrointestinal disorders, wherein substantialidentity between the blood level of the metabolites in the subject andthe reference level indicates that the subject is susceptible to theprobiotic treatment.

In some embodiments, the method includes adjusting the composition ofgut microbiota of the subject.

In some embodiments, adjusting the composition of gut microbiota of thesubject comprises administering the subject a composition comprisingBacteroides bacteria. In some embodiments, the Bacteroides bacteria isB. fragilis, B. thetaiotaomicron, B. vulgatus, or a mixture thereof.

In some embodiments, adjusting the composition of gut microbiota of thesubject comprises fecal transplantation.

In some embodiments, the B. fragilis-responsive metabolite is one of themetabolites listed in Table 2.

Some embodiments disclosed herein are related to a method for relievinggastrointestinal (GI) distress of a subject suffering from autismspectrum disorder (ASD), comprising reducing intestinal permeability inthe subject. In some embodiments, the GI distress comprises abdominalcramps, chronic diarrhea, constipation, intestinal permeability, or acombination thereof. In some embodiments, reducing intestinalpermeability comprises adjusting the composition of gut microbiota inthe subject.

Also disclosed herein in some embodiments is a method for diagnosingautism spectrum disorder (ASD) in a subject, where the method includes:determining the level of a cytokine in gut and the blood level of one ormore ASD-related metabolites in the subject; and detecting whether ornot there is an alteration in the level of the cytokine in gut and theblood level of at least one or more of the ASD-related metabolites inthe subject as compared to a reference level of the cytokine and themetabolite in non-autistic subjects, whereby an alteration in the amountof the cytokine in gut and the blood level of at least one of the one ormore metabolites indicates that the subject suffers from ASD.

Further disclosed herein in some embodiments is a method for diagnosingautism spectrum disorder (ASD) in a subject, where the method includes:determining the blood level of two or more ASD-related metabolites inthe subject; and detecting whether or not there is an alteration in theblood level of the two or more ASD-related metabolites in the subject ascompared to a reference level of the metabolites in non-autisticsubjects, whereby an alteration in the blood level of at least two ofthe two or more ASD-related metabolites indicates that the subjectsuffers from ASD.

In some embodiments, the one or more of the ASD-related metabolites areselected from the metabolites listed in Table 1. In some embodiments,the one or more ASD-related metabolites comprises a metabolite involvedin tryptophan metabolism, a metabolite involved in fatty acidmetabolism, a metabolite involved in purine metabolism, glycolate,imidazole propionate, N-acetylserine, or any combination thereof. Insome embodiments, the metabolite involved in tryptophan metabolism is4-ethylphenylsulfate, indolepyruvate, indolyl-3-acryloylglycine, orserotonin. In some embodiments, the cytokine is interleukin-6 (IL-6). Insome embodiments, the method includes altering the level of one or moreASD-related metabolites in the subject to improve behavioral performancein the subject if it is indicated that the subject suffers from ASD.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. MIA offspring exhibit deficient GI barrier integrity andabnormal expression of tight junction components and cytokines. FIG. 1A.Intestinal permeability assay, measuring fluorescence intensity offluorescein isothiocyanate (FITC) detected in serum after oral gavage ofFITC-dextran. DSS: n=6, S: adult n=16; adolescent n=4, P: adult n=17;adolescent n=4. Data are normalized to fluorescence intensity observedin adult saline offspring. FIG. 1B. Expression of tight junctioncomponents relative to beta-actin in colons of adult saline andpoly(I:C) offspring. Data for each gene are normalized to expressionlevels in saline offspring. n=8. FIG. 1C. Expression of cytokines andinflammatory markers relative to beta-actin in colons of adult salineand poly(I:C) offspring. Data for each gene are normalized to expressionlevels in saline offspring. n=6-21. FIG. 1D. Protein levels of cytokinesand chemokines relative to total protein content in colons of adultsaline and poly(I:C) offspring. n=10. Data are presented as mean±SEM.*p<0.05, **p<0.01, ***p<0.001. DSS=dextran sodium sulfate,S=saline+vehicle, P=poly(I:C)+vehicle. For each experiment, adult salineand poly(I:C) offspring were treated with vehicle at 3 weeks of age, anddata were collected simultaneously for poly(I:C)+B. fragilis treatmentgroup.

FIG. 2. B. fragilis treatment has little effect on tight junctionexpression and cytokine profiles in the small intestine. FIG. 2A.Expression of tight junction components relative to beta-actin in smallintestines of adult saline and poly(I:C) offspring. Data for each geneare normalized to expression levels in saline offspring. n=8. FIG. 2B.Quantification of the effect of B. fragilis treatment on expression ofnotable tight junction components relative to beta-actin in smallintestines of MIA offspring. Data for saline and poly(I:C) are as inpanel (A). n=8. FIG. 2C. Protein levels of cytokines and chemokinesrelative to total protein content in small intestines of adult saline,poly(I:C) and poly(I:C)+B. fragilis offspring. Data is normalized toexpression levels in saline offspring. Asterisks directly above barsindicate significance compared to saline control (normalized to 1, asdenoted by the black line), whereas asterisks at the top of the graphdenote statistical significance between poly(I:C) and poly(I:C)+B.fragilis groups. n=8-10. Data are presented as mean±SEM. *p<0.05,**p<0.01, S=saline+vehicle, P=poly(I:C)+vehicle, P+BF=poly(I:C)+B.fragilis

FIG. 3. B. fragilis treatment has no effect on systemic immunedysfunction in MIA offspring. FIG. 3A. Percent frequency of Foxp3+ CD25+T regulatory cells from a parent population of CD4+ TCRb+ cells,measured by flow cytometry of splenocytes from adult saline, poly(I:C)and poly(I:C)+B. fragilis offspring. n=5. FIG. 3B. Percent frequency ofCD4+ T helper cells and CD11b+ and Gr-1+ neutrophilic and monocyticcells from a parent population of TER119− cells, measured by flowcytometry of splenocytes from adult saline, poly(I:C) and poly(I:C)+B.fragilis offspring. n=5. FIG. 3C. Production of IL-17 and IL-6 bysplenic CD4+ T cells isolated from adult saline and poly(I:C) offspring,after in vitro stimulation with PMA/ionomycin. Treatment effects wereassessed by repeated measures two-way ANOVA with Bonferroni post-hoctest. n=5. FIG. 3D. Production of IL-17 and IL-6 by CD4+ T cellsisolated from mesenteric lymph nodes of adult saline and poly(I:C)offspring, after in vitro stimulation with PMA/ionomycin. Treatmenteffects were assessed by repeated measures two-way ANOVA with Bonferronipost-hoc test. n=5. FIG. 3E. Anxiety-like and locomotor behavior in theopen field exploration assay for adult MIA offspring treated with mutantB. fragilis lacking production of polysaccharide A (PSA). Data indicatetotal distance traveled in the 50×50 cm open field (right), durationspent in the 17×17 cm center square (middle) and number of entries intothe center square (left) over a 10-minute trial. Data for saline,poly(I:C) and poly(I:C)+B. fragilis groups are as in FIG. 10.poly(I:C)+B. fragilis with PSA deletion: n=17. FIG. 3F. Repetitiveburying of marbles in a 6×8 array in a 10-minute trial. Data for saline,poly(I:C) and poly(I:C)+B. fragilis groups are as in FIG. 10.poly(I:C)+B. fragilis with PSA deletion: n=17. Data are presented asmean±SEM. *p<0.05, **p<0.01, ***p<0.001. S=saline+vehicle,P=poly(I:C)+vehicle, P+BF=poly(I:C)+B. fragilis, P+BFΔPSA=poly(I:C)+B.fragilis with PSA deletion.

FIG. 4. MIA induces alterations in the composition of the intestinalmicrobiota. FIG. 4A. Richness of the gut microbiota, as illustrated byrarefaction curves plotting Faith's Phylogenetic Diversity (PD) versusthe number of sequences for each treatment group. FIG. 4B. Evenness ofthe gut microbiota, as indicated by the Gini coefficient. FIG. 4C.Levels of B. fragilis 16S sequence (top) and bacterial 16S sequence(bottom) in fecal samples collected at 1, 2, and 3 weeks post treatmentof adult offspring with vehicle or B. fragilis. Germ-free mice colonizedwith B. fragilis were used as a positive control. Data are presented asquantitative RT-PCR cycling thresholds [C(t)], where C(t)>34 (hatchedline) is considered negligible, and for C(t)<34, lesser C(t) equates tostronger abundance. n=1, where each represents pooled sample from 3-5independent cages. FIG. 4D. Levels of B. fragilis 16S sequence (top) andbacterial 16S sequence (bottom) in fecal samples collected at 1, 2, and3 weeks post treatment of adult offspring with vehicle or B. fragilis.Germ-free mice colonized with B. fragilis were used as a positivecontrol. Data are presented as quantitative RT-PCR cycling thresholds[C(t)], where C(t)>34 (hatched line) is considered negligible, and forC(t)<34, lesser C(t) equates to stronger abundance. n=1, where eachrepresents pooled sample from 3-5 independent cages. Data are presentedas mean±SEM. S=saline+vehicle, P=poly(I:C)+vehicle, P+BF=poly(I:C)+B.fragilis, GF+BF=germ-free+B. fragilis.

FIGS. 5A-E. MIA offspring exhibit dysbiosis of the intestinalmicrobiota. FIG. 5A is an unweighted UniFrac-based 3D PCoA plot based onall OTUs, illustrating global differences in the gut microbiota betweenadult MIA and control offspring. The percent variation explained by eachprincipal coordinate (PC) is indicated on the axes. FIG. 5B is anunweighted UniFrac-based 3D PCoA plot based on subsampling of Clostridiaand Bacteroidia OTUs (2003 reads per sample). FIG. 5C is an unweightedUniFrac-based 3D PCoA plot based on subsampling of OTUs remaining aftersubtraction of Clostridia and Bacteroidia OTUs (47 reads per sample).FIG. 5D is a heat-map showing the relative abundance of unique OTUs ofthe gut microbiota (bottom, x-axis) for individual biological replicatesfrom adult saline and poly(I:C) offspring (right, y-axis), where red ofincreasing intensity denotes increasing relative abundance of a uniqueOTU for a particular sample. All OTUs that significantly discriminatebetween treatment groups are plotted. Family-level taxonomic assignmentsas designated by the Ribosomal Database Project are indicated for eachOTU. FIG. 5E shows mean relative abundance of OTUs classified bytaxonomic assignments at the class level for the most abundant taxa(left) and least abundant taxa (right). n=10. Data were simultaneouslycollected and analyzed for poly(I:C)+B. fragilis treatment group.

FIG. 6. B. fragilis treatment corrects deficits in GI barrier integrityand colon expression of tight junction components and cytokines in MIAoffspring. FIG. 6A. Intestinal permeability assay, measuringfluorescence intensity of fluorescein isothiocyanate (FITC) detected inserum after oral gavage of FITC-dextran. Data are normalized tofluorescence intensity observed in adult saline offspring. Data for DSS,saline and poly(I:C) are as in FIG. 1. poly(I:C)+B. fragilis: n=9. FIG.6B. Expression of tight junction components relative to beta-actin incolons of adult saline, poly(I:C) and poly(I:C)+B. fragilis offspring.Data for each gene are normalized to expression levels in salineoffspring. Data for saline and poly(I:C) are as in FIG. 1. Asterisksdirectly above bars indicate significance compared to saline control(normalized to 1, as denoted by the black line), whereas asterisks atthe top of the graph denote statistical significance between poly(I:C)and poly(I:C)+B. fragilis groups. n=8. FIG. 6C. Immunofluorescencestaining for claudin 8. Representative images for n=5. FIG. 6D. Proteinlevels of claudin 8 (left) and claudin 15 (right) in colons from saline,poly(I:C) and poly(I:C)+B. fragilis offspring, as measured by Westernblot. Representative signals from the same blot are depicted below. Dataare normalized to signal intensity detected in saline offspring. n=3.FIG. 6E. Expression of IL-6 relative to beta-actin in colons of adultsaline, poly(I:C) and poly(I:C)+B. fragilis offspring. Data isnormalized to expression levels in saline offspring. Data for saline andpoly(I:C) are as in FIG. 1. poly(I:C)+B. fragilis: n=3. FIG. 6F. Proteinlevels of cytokines and chemokines relative to total protein content incolons of adult saline, poly(I:C) and poly(I:C)+B. fragilis offspring.Data is normalized to expression levels in saline offspring. Data forsaline and poly(I:C) are as in FIG. 1. Asterisks directly above barsindicate significance compared to saline control (normalized to 1, asdenoted by the black line), whereas asterisks at the top of the graphdenote statistical significance between poly(I:C) and poly(I:C)+B.fragilis groups. n=10. Data are presented as mean±SEM. *p<0.05,**p<0.01, ***p<0.001, n.s.=not significant. DS S=dextran sodium sulfate,S=saline+vehicle, P=poly(I:C)+vehicle, P+BF=poly(I:C)+B. fragilis.

FIG. 7. IL-6 modulates colon expression of claudin 8 and 15. FIG. 7A.Dose-dependent expression of claudin 8 (left) and claudin 15 (right)relative to beta-actin in colons of adult wild-type mice cultured for 4hours ex vivo with increasing concentrations of recombinant mouse IL-6.Data are normalized to expression levels detected in 0 ng/ml IL-6controls. n=3. FIG. 7B. Time-dependent expression of claudin 8 (left)and claudin 15 (right) relative to beta-actin in colons of adultwild-type mice cultured with 80 ng/ml recombinant mouse IL-6. n=3. FIG.7C. Expression of claudin 8 (top) and claudin 15 (bottom) relative tobeta-actin in colons of adult wild-type mice at 12 hours post treatmentwith recombinant mouse IL-6. n=3. Data are presented as mean±SEM.

FIG. 8. B. fragilis treatment alters the composition of the intestinalmicrobiota and corrects species-level abnormalities in MIA offspring.FIG. 8A is an unweighted UniFrac-based 3D PCoA plot based on all OTUs.The percent variation explained by each principal coordinate (PC) isindicated on the axes. Data for saline and poly(I:C) are as in FIG. 2.FIG. 8B. Relative abundance of key OTUs of the family Lachnospiraceae(top) and order Bacteroidales (bottom) that are significantly altered byMIA and completely restored by B. fragilis treatment. Data are presentedas mean±SEM. FIG. 8C is a phylogenetic tree based on nearest-neighboranalysis of 16S rRNA gene sequences for key OTUs presented in panel B.Clades shown in solid lines indicate OTUs of the family Lachnospiraceaeand clades showing in broken lines indicate OTUs of the orderBacteriodales. The 6 taxa labeled with numbers indicate OTUs that aresignificantly elevated in poly(I:C) offspring and corrected by B.fragilis treatment. n=10.

FIG. 9. There is no evidence for persistent colonization of B. fragilisafter treatment of MIA offspring. FIG. 9A. Levels of B. fragilis 16Ssequence (top) and bacterial 16S sequence (bottom) in fecal samplescollected at 1, 2, and 3 weeks post treatment of adult offspring withvehicle or B. fragilis. Germ-free mice colonized with B. fragilis wereused as a positive control. Data are presented as quantitative RT-PCRcycling thresholds [C(t)], where C(t)>34 (hatched line) is considerednegligible, and for C(t)<34, lesser C(t) equates to stronger abundance.n=1, where each represents pooled sample from 3-5 independent cages.FIG. 9B. Levels of B. fragilis 16S sequence (top) and bacterial 16Ssequence (bottom) in fecal samples collected at 1, 2, and 3 weeks posttreatment of adult offspring with vehicle or B. fragilis. Germ-free micecolonized with B. fragilis were used as a positive control. Data arepresented as quantitative RT-PCR cycling thresholds [C(t)], whereC(t)>34 (hatched line) is considered negligible, and for C(t)<34, lesserC(t) equates to stronger abundance. n=1, where each represents pooledsample from 3-5 independent cages. Data are presented as mean±SEM.S=saline+vehicle, P=poly(I:C)+vehicle, P+BF=poly(I:C)+B. fragilis,GF+BF=germ-free+B. fragilis.

FIG. 10. B. fragilis treatment ameliorates autism-related behavioralabnormalities in MIA offspring. FIG. 10A. Anxiety-like and locomotorbehavior in the open field exploration assay, as measured by totaldistance traveled in the 50×50 cm open field (right), duration spent inthe 17×17 cm center square (middle), and number of entries into thecenter of the field (left) over a 10 minute trial. n=35-75. FIG. 10B.Sensorimotor gating in the pre-pulse inhibition assay, as measured bypercent difference between the startle response to pulse only andstartle response to pulse preceded by a 5 db or 15 db pre-pulse.Treatment effects were assessed by repeated measures two-way ANOVA withBonferroni post-hoc test. n=35-75. FIG. 10C. Repetitive burying ofmarbles in a 3×6 array during a 10 minute trial. n=16-45. FIG. 10D.Communicative behavior, as measured by total number (left), averageduration (middle) and total duration (right) of ultrasonic vocalizationsproduced by adult male mice during a 10 minute social encounter. n=10.FIG. 10E shows deficits in sociability in B. fragilis-treated MIAoffspring. FIG. 10F shows deficits in social preference in B.fragilis-treated MIA offspring. Graphs represent cumulative resultsobtained for 3-6 independent cohorts of mice. Data are presented asmean±SEM. *p<0.05, **p<0.01, ***p<0.001. S=saline+vehicle,P=poly(I:C)+vehicle, P+BF=poly(I:C)+B. fragilis. Data were collectedsimultaneously for poly(I:C)+B. fragilis ΔPSA and poly(I:C)+B.thetaiotaomicron treatment groups.

FIG. 11. Amelioration of autism-related behaviors in MIA offspring isnot specific to B. fragilis treatment. FIG. 11A. Anxiety-like andlocomotor behavior in the open field exploration assay, as measured bytotal distance traveled in the 50×50 cm open field (right), durationspent in the 17×17 cm center square (middle), and number of entries intothe center of the field (left) over a 10 minute trial. Poly(I:C)+B.thetaiotaomicron: n=32. FIG. 11B. Repetitive burying of marbles in a 3×6array during a 10 minute trial. Poly(I:C)+B. thetaiotaomicron: n=32.FIG. 11C. Communicative behavior, as measured by total number (left),average duration (middle) and total duration (right) of ultrasonicvocalizations produced by adult male mice during a 10 minute socialencounter. Poly(I:C)+B. thetaiotaomicron: n=10. FIG. 11D. Sensorimotorgating in the pre-pulse inhibition assay, as measured by percentdifference between the startle response to pulse only and startleresponse to pulse preceded by a 5 db or 15 db pre-pulse. Treatmenteffects were assessed by repeated measures two-way ANOVA with Bonferronipost-hoc test. Poly(I:C)+B. thetaiotaomicron: n=32. For all panels, datafor saline, poly(I:C) and poly(I:C)+B. fragilis are as in FIG. 10.Graphs represent cumulative results obtained for 3-6 independent cohortsof mice. Data are presented as mean±SEM. *p<0.05, **p<0.01, ***p<0.001.S=saline+vehicle, P=poly(I:C)+vehicle, P+BF=poly(I:C)+B. fragilis,P+BT=Poly(I:C)+B. thetaiotaomicron.

FIGS. 12A-B. B. fragilis treatment causes statistically significantalterations serum metabolites, with widespread changes in biochemicalsrelevant to fatty acid metabolism and purine salvage pathways. Levels of103 metabolites that are significantly altered in sera of B.fragilis-treated MIA offspring compared to saline controls, as measuredby GC/LC-MS. Colors indicate fold change relative to metaboliteconcentrations detected in saline offspring, where red hues representincreased levels compared to controls and green hues represent decreasedlevels compared to controls (see legend on top left). All changesindicated are p<0.05 by two-way ANOVA with contrasts. P=poly(I:C),P+BF=poly(I:C)+B. fragilis. n=8.

FIG. 13. B. fragilis treatment corrects MIA-induced alterations in4-ethylphenylsulfate (4EPS), a microbe-dependent metabolite thatsufficiently induces anxiety-like behavior. FIG. 13A shows relativequantification of metabolites detected by GC/LC-MS that weresignificantly altered by MIA and restored by B. fragilis treatment. n=8.FIG. 13B shows concentrations of 4EPS detected by LC-MS in sera of adultgerm-free (GF) versus conventionally-colonized (specific pathogen-free,SPF) mice. U.D.=undetectable. n=1, where each represents pooled serafrom 3-5 mice. FIG. 13C. Anxiety-like and locomotor behavior in the openfield exploration assay for conventional wild-type mice treated with4EPS or saline vehicle. Data indicate total distance traveled in the50×50 cm open field (right) and duration spent in the 17×17 cm centersquare (left) over a 10 minute trial. There is no difference between4EPS− and vehicle-treated mice in number of entries into the center ofthe field (data not shown). n=10. FIG. 13D. Potentiated startle reflexin the pre-pulse inhibition assay in 4EPS-treated mice compared tocontrols. Data show the average intensity of startle in response to a120 db pulse (left) and percent inhibition of the pulse when it ispreceded by a 5 db or 15 db pre-pulse (right). n=10. Data are presentedas mean±SEM. *p<0.05, **p<0.01, S=saline+vehicle, P=poly(I:C)+vehicle,P+BF=poly(I:C)+B. fragilis, SPF=specific pathogen-free(conventionally-colonized), GF=germ-free, Veh.=vehicle (saline),4EPS=4-ethylphenylsulfate.

FIGS. 14A-B. Synthesis of autism-associated metabolites by host-microbeinteractions. FIG. 14A. Diagram illustrating the synthesis of 4EPS(found elevated in MIA serum and restored by B. fragilis treatment) andp-cresol (reported to be elevated in urine of individuals with ASD) bymicrobial tyrosine metabolism and host sulfation. FIG. 14B. Diagramillustrating the synthesis of indolepyruvate (found elevated in MIAserum and restored by B. fragilis treatment) andindolyl-3-acryloylglycine (reported to be elevated in urine ofindividuals with ASD) from microbial tryptophan metabolism and hostglycine conjugation. Solid arrows represent known biologicalconversions. Dotted arrow represents predicted biological conversions.

FIGS. 15A-E. 4-ethylphenylsulfate (4EPS) synthesis, detection and invivo experiments. FIG. 15A. Diagram of 4EPS synthesis by treating4-ethylphenol with sulfur trioxide-pyridine in refluxing benzene togenerate the pyridinium salt followed by ion exchange over K+ resin togenerate the potassium salt. FIG. 15B. Dose-response curve and linearregression analysis for known concentrations of potassium 4EPS analyzedby LC/MS. FIG. 15C. Time-dependent increases in serum 4EPS after asingle i.p. injection of 30 mg/kg potassium 4EPS into adult wild-typemice. FIG. 15D. Communicative behavior, as measured by total number(left), average duration (middle) and total duration (right) ofultrasonic vocalizations produced by adult male mice during a 10-minutesocial encounter. n=5. FIG. 15E. Repetitive burying of marbles in a 3×6array during a 10-minute trial. n=10. Data are presented as mean±SEM.Veh.=vehicle (saline), 4EPS=4-ethylphenylsulfate.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe Figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

Autism spectrum disorder (ASD) is a serious neurodevelopmental disordercharacterized by stereotypic behaviors and deficits in language andsocial interaction. As described herein, various metabolites are relatedto ASD. The level of these metabolites in a subject can be determinedand used to diagnose ASD, or adjusted for treating ASD, such as byimproving behavioral performance of the subject. In addition, asdescribed herein, various metabolites are responsive to B. fragilistreatment, and those metabolites can be used to assess thesusceptibility of a subject suffering from ASD to probiotic treatment.

In some embodiments, the level of the metabolite in the circulation of asubject in need of treatment is determined and adjusted to improvebehavioral performance in the subject. The subject in need of treatmentcan be a subject suffering from anxiety, ASD, or a pathologicalcondition with one or more of the symptoms of ASD. The level of themetabolite in the circulation of the subject can be the blood level, forexample the serum level or plasma level, of the metabolite. In someembodiments, the urine or fecal level of the metabolite in the subjectis determined and adjusted to improve behavioral performance in thesubject.

In some embodiments, the level of the metabolite in the circulation of asubject is detected and compared with a reference level of themetabolite in non-autistic population to diagnose whether the subjecthas ASD or not. The level of the metabolite in the circulation of thesubject can be the blood level, for example the serum level or plasmalevel, of the metabolite.

DEFINITIONS

Unless defined otherwise, technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which the present disclosure belongs. See, e.g. Singleton etal., Dictionary of Microbiology and Molecular Biology 2nd ed., J. Wiley& Sons (New York, N.Y. 1994); Sambrook et al., Molecular Cloning, ALaboratory Manual, Cold Springs Harbor Press (Cold Springs Harbor, N.Y.1989). For purposes of the present disclosure, the following terms aredefined below.

As used herein, the term “subject” is a vertebrate, such as a mammal.The term “mammal” is defined as an individual belonging to the classMammalia and includes, without limitation, humans, domestic and farmanimals, and zoo, sports, or pet animals, such as sheep, dogs, horses,cats or cows. In some embodiments, the subject is human.

As used herein, the term “condition/disorder/symptom” or “behavioralabnormality” refers to a symptom expressed by a subject including butnot limited to anxiety, Fragile X, Rett syndrome, tuberous sclerosis,obsessive compulsive disorder, attention deficit disorder,schizophrenia, autistic disorder (classic autism), Asperger's disorder(Asperger syndrome), pervasive developmental disorder not otherwisespecified (PDD-NOS), childhood disintegrative disorder (CDD), or apathological condition with one or more of the symptoms of ASD.

As used herein, the term “subject in need of the treatment” refers to asubject expressing or suffering from one or more of the behavioraldisorder/symptoms mentioned above. An appropriately qualified person isable to identify such an individual in need of treatment using standardbehavioral testing protocols/guidelines. The same behavioral testingprotocols/guidelines can also be used to determine whether there isimprovement to the individual's disorder and/or symptoms.

As used herein, the term “improvement in behavioral performance” refersprevention or reduction in the severity or frequency, to whateverextent, of one or more of the behavioral disorders, symptoms and/orabnormalities expressed by individual suffering from anxiety, ASD, or apathological condition with one or more of the symptoms of ASD.Non-limiting examples of the behavioral symptom include repetitivebehavior, decreased prepulse inhibition (PPI), and increased anxiety.The improvement is either observed by the individual taking thetreatment themselves or by another person (medical or otherwise).

As used herein, the term “treatment” refers to a clinical interventionmade in response to a disease, disorder or physiological conditionmanifested by a patient, particularly a patient suffering from ASD. Theaim of treatment may include, but is not limited to, one or more of thealleviation or prevention of symptoms, slowing or stopping theprogression or worsening of a disease, disorder, or condition and theremission of the disease, disorder or condition. In some embodiments,“treatment” refers to both therapeutic treatment and prophylactic orpreventative measures. Those in need of treatment include those alreadyaffected by a disease or disorder or undesired physiological conditionas well as those in which the disease or disorder or undesiredphysiological condition is to be prevented. For example, in someembodiments treatment may improve behavioral performance of the subject,including ASD-related behaviors. As used herein, the term “prevention”refers to any activity that reduces the burden of the individual laterexpressing those behavioral symptoms. This takes place at primary,secondary and tertiary prevention levels, wherein: a) primary preventionavoids the development of symptoms/disorder/condition; b) secondaryprevention activities are aimed at early stages of thecondition/disorder/symptom treatment, thereby increasing opportunitiesfor interventions to prevent progression of thecondition/disorder/symptom and emergence of symptoms; and c) tertiaryprevention reduces the negative impact of an already establishedcondition/disorder/symptom by, for example, restoring function and/orreducing any condition/disorder/symptom or related complications.

“Pharmaceutically acceptable” carriers are ones which are nontoxic tothe cell or mammal being exposed thereto at the dosages andconcentrations employed. “Pharmaceutically acceptable” carriers can be,but not limited to, organic or inorganic, solid or liquid excipentswhich is suitable for the selected mode of application such as oralapplication or injection, and administered in the form of a conventionalpharmaceutical preparation, such as solid such as tablets, granules,powders, capsules, and liquid such as solution, emulsion, suspension andthe like. Often the physiologically acceptable carrier is an aqueous pHbuffered solution such as phosphate buffer or citrate buffer. Thephysiologically acceptable carrier may also comprise one or more of thefollowing: antioxidants including ascorbic acid, low molecular weight(less than about 10 residues) polypeptides, proteins, such as serumalbumin, gelatin, immunoglobulins; hydrophilic polymers such aspolyvinylpyrrolidone, amino acids, carbohydrates including glucose,mannose, or dextrins, chelating agents such as EDTA, sugar alcohols suchas mannitol or sorbitol, salt-forming counterions such as sodium, andnonionic surfactants such as Tween™, polyethylene glycol (PEG), andPluronics™. Auxiliary, stabilizer, emulsifier, lubricant, binder, pHadjustor controller, isotonic agent and other conventional additives mayalso be added to the carriers.

The pharmaceutically acceptable or appropriate carrier may include othercompounds known to be beneficial to an impaired situation of the GItract, (e.g., antioxidants, such as Vitamin C, Vitamin E, Selenium orZinc); or a food composition. The food composition can be, but is notlimited to, milk, yoghurt, curd, cheese, fermented milks, milk basedfermented products, ice-creams, fermented cereal based products, milkbased powders, infant formulae, tablets, liquid bacterial suspensions,dried oral supplement, or wet oral supplement.

As used herein, the term “neutraceutical” refers to a food stuff (as afortified food or a dietary supplement) that provides health benefits.Nutraceutical foods are not subject to the same testing and regulationsas pharmaceutical drugs.

As used herein, the term “probiotic” refers to live microorganisms,which, when administered in adequate amounts, confer a health benefit onthe host. The probiotics may be available in foods and dietarysupplements (for example, but not limited to capsules, tablets, andpowders). Non-limiting examples of foods containing probiotic includedairy products such as yogurt, fermented and unfermented milk,smoothies, butter, cream, hummus, kombucha, salad dressing, miso,tempeh, nutrition bars, and some juices and soy beverages.

As used herein, the term “metabolite” refers to any molecule involved inmetabolism. Metabolites can be products, substrates, or intermediates inmetabolic processes. For example, the metabolite can be a primarymetabolite, a secondary metabolite, an organic metabolite, or aninorganic metabolite. Metabolites include, without limitation, aminoacids, peptides, acylcarnitines, monosaccharides, lipids andphospholipids, prostaglandins, hydroxyeicosatetraenoic acids,hydroxyoctadecadienoic acids, steroids, bile acids, and glycolipids andphospholipids.

As used herein, the term “cytokine” refers to a secreted protein oractive fragment or mutant thereof that modulates the activity of cellsof the immune system. Examples of cytokines include, without limitation,interleukins, interferons, chemokines, tumor necrosis factors,colony-stimulating factors for immune cell precursors, and the like.

As used herein, the term “antibody” includes polyclonal antibodies,monoclonal antibodies (including full length antibodies which have animmunoglobulin Fc region), antibody compositions with polyepitopicspecificity, multispecific antibodies (e.g., bispecific antibodies,diabodies, and single-chain molecules, and antibody fragments (e.g., Fabor F(ab′)₂, and Fv). For the structure and properties of the differentclasses of antibodies, see e.g., Basic and Clinical Immunology, 8thEdition, Daniel P. Sties, Abba I. Terr and Tristram G. Parsolw (eds),Appleton & Lange, Norwalk, Conn., 1994, page 71 and Chapter 6.

Autism Spectrum Disorder (ASD)

Autism spectrum disorders (ASDs) are complex neurodevelopmentaldisabilities characterized by stereotypic behaviors and deficits incommunication and social interaction. The term “spectrum” refers to thewide range of symptoms, skills, and levels of impairment, or disability,that patients with ASD can have. ASD is generally diagnosed according toguidelines listed in the Diagnostic and Statistical Manual of MentalDisorders, Fourth Edition—Text Revision (DSM-IV-TR). The manualcurrently defines five disorders, sometimes called pervasivedevelopmental disorders (PDDs), as ASD, including Autistic disorder(classic autism), Asperger's disorder (Asperger syndrome), Pervasivedevelopmental disorder not otherwise specified (PDD-NOS), Rett'sdisorder (Rett syndrome), and Childhood disintegrative disorder (CDD).Some patients are mildly impaired by their symptoms, but others areseverely disabled. ASD encompasses a set of complex disorders withpoorly defined etiologies, and no targeted cure

Recent studies highlight striking neural and peripheral immunedysregulation in autistic individuals. Among several comorbidities inASD, gastrointestinal (GI) distress is of particular interest, given itsprevalence and correlation with the severity of core autism behaviors(Adams et al., 2011; Buie et al., 2010; Coury et al., 2012; Gorrindo etal., 2013; Ibrahim et al., 2009; Wang et al., 2011). A significantsubset of ASD children exhibit gastrointestinal (GI) complications,including increased intestinal permeability (or “leaky gut” and alteredcomposition of intestinal microbiota (Buie et al., 2010; Coury et al.,2012; D'Eufemia et al., 1996; de Magistris et al., 2010; de Magistris etal., 2013; Ibrahim et al., 2009). Moreover, a recent multicenter studyof over 14,000 ASD individuals reports a higher prevalence ofinflammatory bowel disease (IBD) and other GI disorders in ASD patientscompared to controls (Kohane et al., 2012). Altered nutrient intake,food allergies and metabolic disruptions are also associated with ASD,and antibiotic treatment and restricted diet are reported to providebehavioral improvements for some autistic children (Buie et al., 2010).

Maternal immune activation (MIA) is an important environmental riskfactor for ASD. Several large epidemiological studies have linkedmaternal viral and bacterial infection with increased autism risk in theoffspring ((Atladottir et al., 2010; Gorrindo et al., 2012). Modelingthis risk factor in mice by injecting pregnant females with the viralmimic poly(I:C) has been show to yield offspring that exhibit the corebehavioral symptoms of autism, including the hallmark symptoms ofrepetitive/compulsive behaviors, as well as a common autismneuropathology (spatially restricted deficits in Purkinje cells)((Boksa, 2010; Malkova et al., 2012; Schwartzer et al., 2013; Shi etal., 2009). Recently, MIA offspring have also been found to exhibitabnormalities in the immune system and the gastrointestinal tract.

Humans are colonized with a great abundance and diversity of microbes,which play a critical role in regulating health and disease. Dysbiosisof the commensal microbiota is implicated in the pathogenesis of severalhuman ailments, including IBD, obesity and cardiovascular disease(Blumberg and Powrie, 2012; Clemente et al., 2012). Commensal bacteriaalso affect a variety of complex behaviors, including social, emotional,nociceptive and anxiety-like behaviors (Amaral et al., 2008; Bravo etal., 2011; Desbonnet et al., 2013; Heijtz et al., 2011), and contributeto brain development and function in mice (Al-Asmakh et al., 2012;Collins et al., 2012; Cryan and Dinan, 2012) and humans (Tillisch etal., 2013). Long-range interactions between the gut microbiota and brainunderlie the ability of microbe-based therapies to treat symptoms ofmultiple sclerosis and depression in mice (Bravo et al., 2011; Hooper etal., 2012; Ochoa-Reparaz et al., 2010) and the reported efficacy ofprobiotics in treating emotional symptoms of chronic fatigue syndromeand psychological distress in humans (Messaoudi et al., 2011; Rao etal., 2009).

Numerous abnormalities related to the microbiota have been identified inautistic individuals, including disrupted community composition (Adamset al., 2011; Finegold, 2011; Finegold et al., 2010; Finegold et al.,2012; Gondalia et al., 2012; Parracho et al., 2005b; Williams et al.,2011; Williams et al., 2012) and altered peripheral levels ofmicrobially-derived metabolites (Altieri et al., 2011; Frye et al.,2013; MacFabe, 2012; Ming et al., 2012b; Yap et al., 2010a).

Methods for Improving Behavioral Performance

Methods for improving behavioral performance in a subject in need oftreatment are provided herein. The subject in need of treatment can be asubject suffering from anxiety, ASD, or a pathological condition withone or more of the symptoms of ASD.

The methods, in some embodiments, include: determining the blood levelof an ASD-related metabolite in a subject in need of treatment; andadjusting the blood level of the ASD-related metabolite in the subjectuntil an improvement in the behavioral performance in the subject isobserved.

The methods, in some embodiments, include: determining the level of anautism spectrum disorder (ASD)-related metabolite in a subject in needof treatment; and adjusting the level of the ASD-related metabolite inthe subject so that the level of the metabolite in the subject issubstantially the same as a reference level of the metabolite innon-autistic subjects, thereby improving behavioral performance in thesubject. In some embodiments, the methods can further includedetermining a reference level of the ASD-related metabolite in apopulation of non-autistic subjects.

In some embodiments, the methods include: determining the level of anautism spectrum disorder (ASD)-related metabolite in a subject in needof treatment; and adjusting the level of the ASD-related metabolite inthe subject so that the level of the metabolite in the subject issubstantially the same as a reference level of the metabolite in apopulation of subjects that do not suffer ASD, anxiety or anypathological condition with one or more of the symptoms of ASD, therebyimproving behavioral performance in the subject. In some embodiments,the methods can further include determining a reference level of theASD-related metabolite in subjects that do not suffer from ASD, anxietyor any pathological condition with one or more of the symptoms of ASD.

The methods disclosed herein, in some embodiments, can also includemeasuring a baseline of behavioral performance prior to adjusting thelevel of the ASD-related metabolite in the subject in need of treatmentand/or measuring the behavioral performance after adjusting the level ofthe ASD-related metabolite in the subject in need of treatment. In someembodiments, the methods can include comparing the behavioralperformance prior to and after adjusting the level of the ASD-relatedmetabolite in the subject in need of treatment, and the comparison canbe used to determine if and to what extent the behavioral performance inthe subject is improved.

In the method disclosed herein, behavioral performance can be measuredand evaluated using various parameters and methods. For example,behavioral test can be conducted to determine the presence and/or extentof restricted repetitive behavior and/or stereotyped behavior patternsof the subject under test. In some embodiments, the Autism BehaviorChecklist (ABC), Autism diagnostic Interview-Revised (ADI-R), childhoodautism Rating Scale (CARS), and/or Pre-Linguistic Autism DiagnosticObservation Schedule (PL-ADOS) is used for the behavioral test. Thebehavioral test can include, but is not limited to, detecting thepresence and/or extent of 1) preoccupation with one or more stereotypedand restricted patterns of interest that is abnormal in either intensityor focus, 2) inflexible adherence to specific, nonfunctional routines orrituals, c) stereotyped and repetitive motor mannerisms (such as handflapping, finger flapping etc.), and/or d) persistent preoccupation withparts of objects. Non-limiting examples of behavior that can be includedin a behavioral test and suggest a need for improving behavioralperformance in the subject under the test include: a) sensory behaviors,including poor use of visual discrimination when learning, seems not tohear, so that a hearing loss is suspected, sometimes shows no “startleresponse” to loud noise”, sometimes painful stimuli such as bruises,cuts, and injections evoke no reaction, often will not blink when brightlight is directed toward eyes, covers ears at many sounds, squints,frowns, or covers eyes when in the presence of natural light, frequentlyhas no visual reaction to a “new” person, stares into space for longperiods of time; b) relating behaviors: frequently does not attend tosocial/environmental stimuli, has no social smile, does not reach outwhen reached for, non-responsive to other people's facialexpressions/feelings, actively avoids eye contact, resists being touchedor held, is flaccid when held in arms, is stiff and hard to held, doesnot imitate other children at play, has not developed any friendships,often frightened or very anxious, “looks through” people; c) body andobject use behaviors: whirls self for long periods of time, does not usetoys appropriately, insists on keeping certain objects with him/her,rocks self for long periods of time, does a lot of lunging and darting,flaps hands, walks on toes, hurts self by banging head, biting hand,etc. . . . , twirls, spins, and bangs objects a lot, will feel, smell,and/or taste objects in the environment, gets involved in complicated“rituals” such as lining things up, etc. . . . , is very destructive;and d) language behaviors: does not follow simple commands given once,has pronoun reversal, speech is atonal, does not respond to own namewhen called out among two others, seldom says “yes” or “I”, does notfollow simple commands involving prepositions, gets desired objects bygesturing, repeats phrases over and over, cannot point to more than fivenamed objects, uses 0-5 spontaneous words per day to communicate wantsand needs, repeats sounds or words over and over, echoes questions orstatements made by others, uses at least 15 but less than 30 spontaneousphrases daily to communicate, learns a simple task but “forgets”quickly, strong reactions to changes in routine/environment, has“special abilities” in one area of development, which seems to rule outmental retardation, severe temper tantrums and/or frequent minortantrums, hurts others by biting, hitting, kicking, etc. . . . , doesnot wait for needs to be met, difficulties with toileting, does notdress self without frequent help, frequently unaware of surroundings,and may be oblivious to dangerous situations, prefers to manipulate andbe occupied with inanimate things, and A developmental delay wasidentified at or before 30 months of age. One of ordinary skill in theart would appreciate that the attending physician would know how toidentify a subject in need of treatment disclosed herein.

After adjustment, the level of the ASD-related metabolite in the subjectcan about 50%, about 60%, about 70%, about 80%, about 90%, about 95%,about 98%, about 99%, about 100%, about 101%, about 102%, about 105%,about 110%, about 120%, about 130%, about 140%, about 150%, or a rangebetween any two of these values of the reference level of the metabolitein non-autistic subjects. In some embodiments, the level of theASD-related metabolite in the subject is about 80%, about 90%, about95%, about 98%, about 99%, about 100%, about 101%, about 102%, about105%, about 110%, about 120%, or a range between any two of these valuesof the reference level of the metabolite in non-autistic subjects. Insome embodiments, the level of the ASD-related metabolite in the subjectis about 95%, about 98%, about 99%, about 100%, about 101%, about 102%,about 105%, or a range between any two of these values of the referencelevel of the metabolite in non-autistic subjects. The level of themetabolite can be the level of the metabolite in circulation of thesubject. For example, the level of the metabolite can be the level ofthe metabolite in blood or other body fluids (e.g., cerebrospinal fluid,pleural fluid, amniotic fluid, semen, or saliva) of the subject. In someembodiments, the level of the metabolite is the blood level of themetabolite in the subject. The blood level of the metabolite can be, forexample, serum level or plasma level of the metabolite. In someembodiments, the level of the metabolite is the urine level of themetabolite in the subject.

In some embodiments, the subject suffers from anxiety, ASD, or apathological condition with one or more of the symptoms of ASD.Non-limiting examples of ASD include Autistic disorder (classic autism),Asperger's disorder (Asperger syndrome), Pervasive developmentaldisorder not otherwise specified (PDD-NOS), Rett's disorder (Rettsyndrome), and Childhood disintegrative disorder (CDD). In someembodiments, the subject suffers from ASD. In some embodiments, thesubject suffers from autism.

Various methods can be used to adjust the level, for example bloodlevel, of the ASD-related metabolite in the subject. In someembodiments, the level, for example blood level, of the metabolite isadjusted by adjusting the composition of gut microbiota in the subject.Adjustment of the composition of gut microbiota in the subject can beachieved by, for example, fecal transplantation (also known as fecalmicrobiota transplantation (FMT), fecal bacteriotherapy or stooltransplant). Fecal transplantation can include a process oftransplantation of fecal bacteria from a healthy donor, for example anon-autistic subject, to a recipient (e.g., a subject suffering fromautism). The procedure of fecal transplantation can include single ormultiple infusions (e.g., by enema) of bacterial fecal flora from thedonor to the recipient.

In some embodiments, adjusting the composition of gut microbiota in thesubject includes administering the subject a composition comprisingbacteria, for example, a composition comprising Bacteroides bacteria.The Bacteroides bacteria that can be used in the method disclosed hereinis not particularly limited. In some embodiments, the Bacteroidesbacteria comprise B. fragilis, B. thetaiotaomicron, B. vulgatus, or amixture thereof. In some embodiments, the Bacteroides bacteria can be B.fragilis. The composition comprising bacteria, for example a compositioncomprising Bacteroides bacteria, can be administered to the subject viavarious routes. For example, the composition can be administered to thesubject via oral administration, rectum administration, transdermaladministration, intranasal administration or inhalation. In someembodiments, the composition is administered to the subject orally. Thecomposition comprising bacteria, such as Bacteroides bacteria, can alsobe in various forms. For example, the composition can be a probioticcomposition, a neutraceutical, a pharmaceutical composition, or amixture thereof. In some embodiments, the composition is a probioticcomposition. Each dosage for human and animal subjects preferablycontains a predetermined quantity of the bacteria calculated in anamount sufficient to produce the desired effect. The actual dosage formswill depend on the particular bacteria employed and the effect to beachieved. The composition comprising bacteria, for example, acomposition comprising Bacteroides bacteria, can be administered aloneor in combination with one or more additional probiotic, neutraceutical,or therapeutic agents. Administration “in combination with” one or morefurther additional probiotic, neutraceutical, or therapeutic agentsincludes both simultaneous (at the same time) and consecutiveadministration in any order. Administration can be chronic orintermittent, as deemed appropriate by the supervising practitioner,particularly in view of any change in the disease state or anyundesirable side effects. “Chronic” administration refers toadministration of the composition in a continuous manner while“intermittent” administration refers to treatment that is done withinterruption.

In some embodiments, adjusting the composition of gut microbiota in thesubject includes reducing the level of one or more bacterial species inthe subject. For example, the level of Clostridia bacteria (such asLachnospiraceae) in the subject can be reduced to adjust the compositionof gut microbiota in the subject. In some embodiments, theLachnospiraceae is Roseburia. The level of Bacterioidia bacteria (suchas Bacteroidales 524-7) can also be reduced to adjust the composition ofgut microbiota in the subject. In some embodiments, the Clostridiabacteria is Lachnospiraceae. Various methods can be used to reduce thelevel of one or more bacteria species in the subject. For example, areduced carbohydrate diet can be provided to the subject to reduce oneor more intestinal bacterial species. Without being bound to anyspecific theory, it is believed that a reduced carbohydrate diet canrestrict the available material necessary for bacterial fermentation toreduce intestinal bacterial species.

In some embodiments, adjusting the composition of gut microbiota in thesubject includes increasing the level of one or more bacterial speciesin the subject. For example, the level of Ruminococcaceae,Erysipelotrichaceae, and/or Alcaligenaceae bacteria in the subject canbe increased to adjust the composition of gut microbiota in the subject.

ASD-Related Metabolites

As used herein, the term “autism spectrum disorder (ASD)-relatedmetabolite” refers to a metabolite whose level is altered in a subjectsuffering from ASD, anxiety, and/or any pathological condition with oneor more of the symptoms of ASD as compared to a non-autistic subjectand/or a subject that does not suffer from ASD, anxiety or anypathological condition with one or more of the symptoms of ASD. Forexample, the level of the metabolite may be altered in circulation ofthe subject suffering from ASD as compared to a non-autistic subject. Insome embodiments, the level of the metabolite is altered in blood,serum, plasma, body fluids (e.g., cerebrospinal fluid, pleural fluid,amniotic fluid, semen, or saliva), urine, and/or feces of the subjectsuffering from ASD as compared to a non-autistic subject. In someinstances, the ASD-related metabolite plays a causative role in thedevelopment of ASD-related behaviors in the subject suffering from ASD.In some instances, the alteration in the level of ASD-related metaboliteis caused by ASD. The ASD-related metabolite can have an increased ordecreased level in the subject suffering from ASD as compared to anon-autistic subject or a subject that does not suffer from ASD, anxietyor any pathological condition with one or more of the symptoms of ASD.

One of ordinary skill in the art will appreciate that variability in thelevel of metabolites may exist between individuals, and a referencelevel can be established as a value representative of the level of themetabolites in a non-autistic population, or a population of subjectsthat do not suffer from ASD, anxiety or any pathological condition withone or more of the symptoms of ASD, for the comparison. Various criteriacan be used to determine the inclusion and/or exclusion of a particularsubject in the reference population, including age of the subject (e.g.the reference subject can be within the same age group as the subject inneed of treatment) and gender of the subject (e.g. the reference subjectcan be the same gender as the subject in need of treatment). In someembodiments, the ASD-related metabolite has an increased level in thesubject suffering from ASD as compared to the reference level. In someembodiments, the ASD-related metabolite has a decreased level in thesubject suffering from ASD as compared to the reference level. In someembodiments, the alteration in the level of ASD-related metabolite canbe restored partially or fully by adjusting the composition of gutmicrobiota in the subject suffering from ASD.

Non-limiting examples of ASD-related metabolites are provided in Table1.

TABLE 1 Exemplary ASD-related metabolites N-acetylserine beta-alanine4-methyl-2-oxopentaoate imidazole phenol sulfate 5-methylthioadenosinepropionate serotonin 3-methyl-2-oxovalerate docosapentaenoate (n3 DPA;22:5n3) arginine ornithine docosapentaenoate (n6 DPA; 22:5n6)glycylvaline eicosenoate dihomo-linoleate (20:2n6) xyloseoctadecanedioate docosahexaenoate (DHA; 22:6n3) stearate pantothenate1-pentadecanoylglycerophosphocholine 13-HODE + 9- ergothioneine1-oleoylglycerophosphoethanolamine HODE bilirubin (E,E) glycolate(hydroxyacetate) 4-ethylphenylsulfate equol sulfate transurocanate1-palmitoylglycerophosphoethanolamine glutamine indolepyruvate1-stearoylglycerophosphoinositol adrenate 3-phosphoglycerate1-palmitoleoylglycerophosphocholine myo-inositol phenylacetylglycine1-palmitoylplasmenylethanolamine cysteine phosphoenolpyruvate PeptideTDTEDKGEFLSEGGGVR ribose 12-HETE 4-methylphenylsulfate 4-methylphenylIndolyl-3-acryloylglycine 4-ethylphenyl

The ASD-related metabolites are involved in various metabolic pathways.Examples of metabolic pathways that the ASD-related metabolite can beinvolved in include, but are not limited to, amino acid metabolism,protein metabolism, carbohydrate metabolism, lipid metabolism, andmetabolism of cofactors and vitamins. For example, the ASD-relatedmetabolite can be a metabolite involved in glycine, serine and threoninemetabolism; alanine and aspartate metabolism; glutamate metabolism;histidine metabolism; phenylalanine and tyrosine metabolism; tryptophanmetabolism; valine, leucine and isoleucine metabolism; cysteine,methionine, SAM, and taurine metabolism; urea cycle; arginine-,proline-metabolism; and/or polyamine metabolism. The ASD-relatedmetabolite can also be a dipeptide or fibrinogen cleavage peptide. Inaddition, the ASD-related metabolite can be a metabolite involved inglycolysis, gluconeogenesis, pyruvate metabolism; and/or nucleotidesugars, pentose metabolism. The ASD-related metabolite can also be ametabolite involved in essential fatty acid, long chain fatty acid,monohydroxy and/or dicarboxylate fatty acid, eicosanoid, inositol,and/or lysolipid metabolism. The ASD-related metabolite can be ametabolite involved in hemoglobin and porphyrin metabolism, pantothenateand CoA metabolism, and/or benzoate metabolism.

In some embodiments, an ASD-related metabolite is a metabolite involvedin tryptophan metabolism, a metabolite involved in fatty acidmetabolism, or a metabolite involved in purine metabolism. In someembodiments, an ASD-related metabolite is glycolate, imidazolepropionate, or N-acetylserine. In some embodiments, an ASD-relatedmetabolite is 4-ethylphenylsulfate (4EPS),4-ethylphenyl, indolepyruvate,indolyl-3-acryloylglycine, or serotonin. In some embodiments, anASD-related metabolite is 4-methylphenylsulfate or 4-methylphenyl.

In some embodiments, the level of one ASD-related metabolite is adjustedor improving behavioral performance in the subject. For example, thelevel of 4EPS or indolepyruvate in the subject, for example the bloodlevel (e.g., serum level) of 4EPS and indolepyruvate, can be adjustedfor improving behavioral performance of the subject. In someembodiments, the level of two or more ASD-related metabolites isadjusted for improving behavioral performance in the subject. Forexample, the level of 4EPS and indolepyruvate in the subject, forexample the blood level (e.g., serum level) of 4EPS and indolepyruvate,can be adjusted for improving behavioral performance of the subject.

Various methods can be used to adjust the level, for example blood level(e.g., serum level) or urine level, of the ASD-related metabolite in thesubject for improving behavioral performance of the subject. Forexample, an antibody that specifically binds the ASD-related metabolite,an intermediate for the in vivo synthesis of the ASD-related metabolite,or a substrate for the in vivo synthesis of the ASD-related metabolitecan be administered to the subject to adjust the level of theASD-related metabolite in the subject. For example, an antibody thatspecifically binds 4EPS and/or one or more of the substrates andintermediates in the in vivo 4EPS synthesis can be used to reduce thelevel of 4EPS in the subject. In some embodiments, an antibody thatspecifically binds tyrosine, hydroxyphenylpyruvic acid, p-coumaric acid,p-vinylphenynol, hydroxyphenylpropionate, and/or 4-ethylphenol isadministered to the subject to reduce the level of 4EPS in the subject.In some embodiments, an antibody that specifically binds 4EPS isadministered to the subject to reduce the level of 4EPS in the subject.As another example, an antibody that specifically binds4-methylphenylsulfate and/or one or more of the substrates andintermediates in the in vivo 4-methylphenylsulfate synthesis can be usedto reduce the level of 4-methylphenylsulfate in the subject. In someembodiments, an antibody that specifically binds tyrosine,hydroxyphenylpyruvic acid, hydroxyphenylpropionate,hydroxyphenylacetate, and/or p-cresol is administered to the subject toreduce the level of 4-methylphenylsulfate, e.g., the urine level of4-methylphenylsulfate, in the subject. In some embodiments, an antibodythat specifically binds 4-methylphenylsulfate is administered to thesubject to reduce the level of 4-methylphenylsulfate in the subject. Asyet another example, an antibody that specifically bindsindolyl-3-acryloylglycine and/or one or more of the substrates andintermediates in the in vivo indolyl-3-acryloylglycine synthesis can beused to reduce the level of indolyl-3-acryloylglycine in the subject. Insome embodiments, an antibody that specifically binds tryptophan,indolepyruvate, and/or indoleacrylic acid is administered to the subjectto reduce the level of indolyl-3-acryloylglycine in the subject. In someembodiments, an antibody that specifically bindsindolyl-3-acryloylglycine is administered to the subject to reduce thelevel of indolyl-3-acryloylglycine in the subject. As still yet anotherexample, an antibody that specifically binds tryptophan andindolepyruvate can be used to reduce the level of indolepyruvate in thesubject.

Methods for generating antibodies that specifically bind small moleculeshave been developed in the art. For example, generation of monoclonalantibodies against small molecules has been described in Rufo et al., J.Ag. Food Chem. 52:182-187 (2004), which is hereby incorporated byreference. For example, an animal such as a guinea pig or rat,preferably a mouse, can be immunized with a small molecule conjugated toa hapten (e.g., KLH), the antibody-producing cells, preferably spleniclymphocytes, can be collected and fused to a stable, immortalized cellline, preferably a myeloma cell line, to produce hybridoma cells whichare then isolated and cloned. See, e.g., U.S. Pat. No. 6,156,882, whichis hereby incorporated by reference. In addition, the genes encoding theheavy and light chains of a small molecule-specific antibody can becloned from a cell, e.g., the genes encoding a monoclonal antibody canbe cloned from a hybridoma and used to produce a recombinant monoclonalantibody.

The level, for example blood level (e.g., serum level) or urine level,of the ASD-related metabolite in the subject can also be adjusted byinhibiting an enzyme involved in the in vivo synthesis of theASD-related metabolite for improving behavioral performance of thesubject.

As described herein, adjusting the level, for example blood level (e.g.,serum level), of the ASD-related metabolite in the subject canameliorate gastrointestinal (GI) distress of the subject suffering fromASD. The GI distress can be abdominal cramps, chronic diarrhea,constipation, intestinal permeability, or a combination thereof. Asdisclosed herein, amelioration is used in a broad sense to refer to atleast a reduction in the magnitude of a parameter, e.g., symptom,associated with the pathological condition being treated. In someembodiments, the method can completely inhibited, e.g., prevented fromhappening, or stopped, e.g., terminated, such that the host no longersuffers from the pathological condition, or at least one or more of thesymptoms that characterize the pathological condition. In someembodiments, the method can delay or slowing of disease progression,amelioration or palliation of the disease state, and remission (whetherpartial or total), whether detectable or undetectable.

As discussed above, gastrointestinal (GI) distress is an importantcomorbidity in ASD, given its prevalence and correlation with theseverity of core autism behaviors. Also disclosed herein are methods forrelieving gastrointestinal (GI) distress of a subject suffering fromASD. The methods can include reducing intestinal permeability in thesubject. In some embodiments, the GI distress comprises abdominalcramps, chronic diarrhea, constipation, intestinal permeability, or acombination thereof. Reducing intestinal permeability can be achieved byaltering the composition of gut microbiota in the subject. In someembodiments, altering the composition of gut microbiota in the subjectcomprises administering the subject a composition comprising bacteria,such as Bacteroides bacteria. In some embodiments, altering thecomposition of gut microbiota in the subject comprises fecaltransplantation. In some embodiments, altering the composition of gutmicrobiota in the subject comprises probiotic treatment.

A variety of subjects are treatable. Generally, such subjects aremammals, where the term is used broadly to describe organisms which arewithin the class mammalia, including the orders carnivore (for example,dogs and cats), rodentia (for example, mice, guinea pigs and rats), andprimates (for example, humans, chimpanzees and monkeys). In preferredembodiments, the subjects are humans.

In the methods disclosed herein, the amount of bacteria, for exampleBacteroides bacteria (e.g., B. fragilis), administered to the subject inneed of treatment can be determined according to various parameters suchas the age, body weight, response of the subject, condition of thesubject to be treated; the type and severity of the anxiety, ASD, or thepathological conditions with one or more symptoms of ASD; the form ofthe composition in which the bacteria is included; the route ofadministration; and the required regimen. The severity of the conditionmay, for example, be evaluated, in part, by standard prognosticevaluation methods. A program comparable to that discussed above may beused in veterinary medicine. For example, the amount of bacteria can betitrated to determine the effective amount for administering to thesubject in need of treatment. One of ordinary skill in the art wouldappreciate that the attending physician would know how to and when toterminate, interrupt or adjust administration of bacteria due totoxicity or organ dysfunctions. Conversely, the attending physicianwould also know to adjust treatment to higher levels if the clinicalresponse were not adequate (precluding toxicity).

Methods for Assessing the Susceptibility of an ASD Subject to ProbioticTreatment

Methods for assessing the susceptibility of a subject suffering from ASDto probiotic treatment are provided herein. The methods can include:determining the level of a B. fragilis-responsive metabolite in thesubject; and comparing the level of the B. fragilis-responsivemetabolite in the subject to a reference level of the metabolite insubjects suffering from ASD and one or more gastrointestinal disorders,wherein substantial identity between the blood level of the metabolitesin the subject and the reference level indicates that the subject issusceptible to the probiotic treatment, for example B. fragilisprobiotic treatment. In some embodiments, the method includesdetermining the level of two or more B. fragilis-responsive metabolitesin the subject; and comparing the level of each of the two or more B.fragilis-responsive metabolites in the subject to the reference level ofeach of the two or more B. fragilis-responsive metabolites, whereinsubstantial identity between the blood levels of the metabolites in thesubject and the reference levels indicates an increased susceptibilityof the subject to the probiotic treatment.

The level of the metabolite can be the level of the metabolite incirculation of the subject. For example, the level of the metabolite isthe level of the metabolite in blood or other body fluids (e.g.,cerebrospinal fluid, pleural fluid, amniotic fluid, semen, or saliva) ofthe subject. In some embodiments, the level of the metabolite is theblood level of the metabolite in the subject. The blood level of themetabolite can be, for example, serum level or plasma level of themetabolite. In some embodiments, the level of the metabolite is theurine level of the metabolite in the subject.

B. fragilis-Responsive Metabolites

As used herein, the term “B. fragilis-responsive metabolite” refers to ametabolite whose level has been determined to be altered by B. fragilistreatment. For example, the level of the metabolite may be altered incirculation of the subject after B. fragilis treatment. In someembodiments, the level of the metabolite is altered in blood, serum,plasma, body fluids (e.g., cerebrospinal fluid, pleural fluid, amnioticfluid, semen, or saliva), urine, and/or feces of the subject after B.fragilis treatment. The B. fragilis-responsive metabolite can beincreased or decreased in level after B. fragilis treatment. In someinstances, the ASD-related metabolite plays a causative role in theimprovement of behavioral performance in the ASD subject treated with B.fragilis. In some instances, a B. fragilis-responsive metabolite is alsoan ASD-related metabolite. In some instances, an ASD-related metaboliteis also a B. fragilis-responsive metabolite.

As disclosed herein, B. fragilis-responsive metabolite can be determinedby comparing the pre-treatment level of a metabolite in a subject, forexample a subject suffering from ASD, with the level of a metabolite inthe subject after B. fragilis treatment. One of ordinary skill in theart will appreciate that variability in the level of metabolites mayexist between individuals, and a reference level for a B.fragilis-responsive metabolite can be established as a valuerepresentative of the level of the metabolites in a population for ASDsubjects suffering from one or more GI disorders for the comparison. Insome embodiments, the B. fragilis-responsive metabolite has an increasedlevel in the subject suffering from ASD as compared to the referencelevel. In some embodiments, the B. fragilis-responsive metabolite has adecreased level in the subject suffering from ASD as compared to thereference level.

Non-limiting examples of B. fragilis-responsive metabolites are providedin Table 2.

TABLE 2 Exemplary B. fragilis-responsive metabolites sarcosine(N-Methylglycine) inosine aspartate adenosine 3-ureidopropionateadenosine 5′-monophosphate (AMP) glutarate (pentanedioate) guanosine 5′-monophosphate (5′-GMP) tyrosine urate 3-(4-hydroxyphenyl)lactate2′-deoxycytidine 3-phenylpropionate (hydrocinnamate) uracil serotonin(5HT) pseudouridine 3-methyl-2-oxobutyrate nicotinamide3-methyl-2-oxovalerate catechol sulfate 4-methyl-2-oxopentanoatesalicylate isobutyrylcarnitine equol sulfate 2-methylbutyroylcarnitineerythritol isovalerylcarnitine dodecanedioate 2-hydroxybutyrate (AHB)tetradecanedioate arginine hexadecanedioate ornithine octadecanedioate2-aminobutyrate undecanedioate 4-guanidinobutanoate 12-HETE 5-oxoprolinepropionylcarnitine glycylvaline butyrylcarnitinegamma-glutamyltryptophan valerylcarnitine TDTEDKGEFLSEGGGV3-dehydrocarnitine TDTEDKGEFLSEGGGVR hexanoylcarnitine sorbitoloctanoylcarnitine pyruvate choline ribitol chiro-inositol ribose pinitolribulose 3-hydroxybutyrate (BHBA) xylitol 1,2-propanediol citrate1-linoleoylglycerophosphoethanolamine fumarate1-arachidonoylglycerophosphoethanolamine malate2-arachidonoylglycerophosphoethanolamine linoleate (18:2n6)1-stearoylglycerophosphoinositol linolenate [alpha or gamma; (18:3n3 or6)] 1-linoleoylglycerophosphoinositol dihomo-linolenate (20:3n3 or n6)1-arachidonoylglycerophosphoinositol docosapentaenoate (n3 DPA; 22:5n3)1-palmitoylplasmenylethanolamine docosapentaenoate (n6 DPA; 22:5n6)hypoxanthine docosahexaenoate (DHA; 22:6n3) eicosenoate (20:1n9 or 11)heptanoate (7:0) dihomo-linoleate (20:2n6) pelargonate (9:0) mead acid(20:3n9) laurate (12:0) adrenate (22:4n6) myristate (14:0)8-hydroxyoctanoate palmitate (16:0) 3-hydroxydecanoate palmitoleate(16:1n7) 16-hydroxypalmitate margarate (17:0) 13-HODE + 9-HODE stearate(18:0) 12,13-hydroxyoctadec-9(Z)-enoate oleate (18:1n9)9,10-hydroxyoctadec-12(Z)-enoic acid stearidonate (18:4n3) adipatesuberate (octanedioate) 2-hydroxyglutarate sebacate (decanedioate)pimelate (heptanedioate) azelate (nonanedioate)

Diagnosis of ASD

Also disclosed herein are methods for diagnosing ASD in a subject. Insome embodiments, the methods include: determining the level of acytokine in gut and the level of one or more ASD-related metabolites inthe subject; and detecting whether or not there is an alteration in thelevel of the cytokine in gut and the level of at least one or more ofthe ASD-related metabolites in the subject as compared to a referencelevel of the cytokine and the metabolite in non-autistic subjects,whereby an alteration in the amount of the cytokine in gut and the levelof at least one of the one or more metabolites indicates that thesubject suffers from ASD.

In some embodiments, the method include: determining the level of anASD-related metabolite in the subject; and detecting whether or notthere is an alteration in the level of the ASD-related metabolite in thesubject as compared to a reference level of the metabolite innon-autistic subjects, whereby an alteration in the level of theASD-related metabolite indicates that the subject suffers from ASD. Insome embodiments, the method include: determining the level of two ormore ASD-related metabolites in the subject; and detecting whether ornot there is an alteration in the level of the two or more ASD-relatedmetabolites in the subject as compared to a reference level of themetabolites in non-autistic subjects, whereby an alteration in the levelof at least two of the two or more ASD-related metabolites indicatesthat the subject suffers from ASD.

As disclosed herein, the level of the ASD-metabolite can be the level ofthe metabolite in circulation of the subject. For example, the level ofthe metabolite can be the level of the metabolite in blood or other bodyfluids (e.g., cerebrospinal fluid, pleural fluid, amniotic fluid, semen,or saliva) of the subject. In some embodiments, the level of themetabolite is the blood level of the metabolite in the subject. Theblood level of the metabolite can be, for example, serum level or plasmalevel of the metabolite. In some embodiments, the level of themetabolite is the urine level of the metabolite in the subject.

One of ordinary skill in the art will appreciate that variability in thelevel of metabolites and/or the level of cytokines may exist betweenindividuals in a non-autistic population. And thus, a reference levelfor the metabolite can be established as a value representative of thelevel of the metabolites in a non-autistic population for thecomparison, and a reference level for the cytokine can be established asa value representative of the level of the cytokine in a non-autisticpopulation for the comparison. In some embodiments, the ASD-relatedmetabolite has an increased level in the subject suffering from ASD ascompared to the reference level of the ASD-related metabolite. In someembodiments, the ASD-related metabolite has a decreased level in thesubject suffering from ASD as compared to the reference level of theASD-related metabolite. In some embodiments, the level of the cytokineis increased in the subject suffering from ASD as compared to thereference level of the cytokine. In some embodiments, the level of thecytokine is decreased in the subject suffering from ASD as compared tothe reference level of the cytokine. The ASD-related metabolites aredescribed herein, and non-limiting examples of the ASD-relatedmetabolites that can be used in the methods are provided in Table 1.

In some embodiments, the cytokine is interleukin-6 (IL-6). In someembodiments, the one or more ASD-related metabolites comprises ametabolite involved in tryptophan metabolism, a metabolite involved infatty acid metabolism, a metabolite involved in purine metabolism,glycolate, imidazole propionate, N-acetylserine, or any combinationthereof. Non-limiting examples of metabolites involved in tryptophanmetabolism include 4-ethylphenylsulfate, indolepyruvate,indolyl-3-acryloylglycine, or serotonin. In some embodiments, theASD-related metabolite is 4-ethylphenylsulfate, indolepyruvate,indolyl-3-acryloylglycine, or serotonin.

In the methods disclosed in the present disclosure, the level of ametabolite in the subject can be determined by any conventional methodsknown in the art, including but not limited to chromatography, liquidchromatography, size exclusion chromatography, high performance liquidchromatography (HPLC), gas chromatography, mass spectrometry, tandemmass spectrometry, matrix assisted laser desorption/ionization-time offlight (MALDI-TOF) mass spectrometry, electrospray ionization (ESI) massspectrometry, surface-enhanced laser deorption/ionization-time of flight(SELDI-TOF) mass spectrometry, quadrupole-time of flight (Q-TOF) massspectrometry, atmospheric pressure photoionization mass spectrometry(APPI-MS), Fourier transform mass spectrometry (FTMS), matrix-assistedlaser desorption/ionization-Fourier transform-ion cyclotron resonance(MALDI-FT-ICR) mass spectrometry, secondary ion mass spectrometry(SIMS), radioimmunoassays, microfluidic chip-based assay, detection offluorescence, detection of chemiluminescence, or a combination thereof.

EXAMPLES

Some aspects of the embodiments discussed above are disclosed in furtherdetail in the following examples, which are not in any way intended tolimit the scope of the present disclosure.

Experimental Material and Methods

The following experimental methods were used for Examples 1-8 describedbelow.

Animals and MIA

Pregnant C57BL/6N (Charles River; Wilmington, Mass.) were selected atrandom from a larger cohort of pregnant females, and injected i.p. onE12.5 with saline or 20 mg/kg poly(I:C) according to the methodsdescribed in Smith et al., 2007. All animal experiments were approved bythe Caltech IACUC.

B. fragilis Treatment

At 3 weeks of age, saline and poly(I:C) offspring across individuallitters were weaned into cages of 4 non-littermate offspring of the sametreatment group to generate a randomized experimental design (Lazic,2013). Cages within the poly(I:C) versus saline treatment groups wereselected at random for treatment with B. fragilis or vehicle, everyother day for 6 days. To preclude any confounding effects of early lifestress on neurodevelopment and behavior, suspensions were notadministered by oral gavage. For B. fragilis treatment, 10̂10 cfu freshlygrown B. fragilis was suspended in 1 mL 1.5% sodium bicarbonate, mixedwith 4 ml sugar-free applesauce and spread over four standard foodpellets. For vehicle treatment, saline and poly(I:C) animals were fed1.5% sodium bicarbonate in applesauce over food pellets. Applesauce andpellets were completely consumed by mice of each treatment group by 48hours after administration. The same procedure was used for treatmentwith mutant B. fragilis lacking PSA and B. thetaiotaomicron.

Intestinal Permeability Assay

Adult mice were fasted for 4 hours before oral gavage with 0.6 g/kg 4kDa FITC-dextran (Sigma Aldrich). 4 hours later, blood samples werecollected by cardiac puncture and spun through SST vacutainers (BectonDickinson). FITC-dextran standards and 3×-diluted sera were immediatelyread for FITC fluorescence intensity at 521 nm using an xFluor4spectrometer (Tecan). Mice were fed 3% dextran sulfate sodium salt (DSS;MP Biomedicals) in drinking water for 7 days to chemically inducecolitis.

In Vitro Immune Assays

Methods for Treg and Gr-1 flow cytometry and CD4+ T cell in vitrostimulation are described in Hsiao et al., 2012. Briefly, cells wereharvested in complete RPMI from spleens and mesenteric lymph nodes. Forsubtyping of splenocytes, cells were stained with Gr-1 APC, CD11b-PE,CD4-FITC and Ter119-PerCP-Cy5.5 (Biolegend). For detection of Tregs,splenocytes were stimulated for 4 hours with PMA/ionomycin in thepresence of GolgiPLUG (BD Biosciences), blocked for Fc receptors andlabeled with CD4-FITC, CD25-PE, Foxp3-APC and Ter119-PerCP-Cy5.5.Samples were processed using the FACSCalibur cytometer (BD Biosciences)and analyzed using FlowJo software (TreeStar). For CD4+ T cellstimulation assays, 10̂6 CD4+ T cells were cultured in complete RPMI withPMA (50 ng/ml) and ionomycin (750 ng/ml) for 3 days at 37° C. with 5%(vol/vol) CO₂. Each day, supernatant was collected for ELISA assays todetect IL-6 and IL-17, according to the manufacturer's instructions(eBioscience).

IL-6 Oral Gavage and In Vitro Colon Culture

For in vivo assays, adult mice were gavaged with 5 ug carrier-freerecombinant mouse IL-6 (eBioscience) in 1.5% sodium bicarbonate. At 4hours post-gavage, 1 cm regions of distal, medial and proximal colonwere dissected, washed in HBSS and processed for qRT-PCR, as describedabove. For in vitro assays, adult mice were sacrificed and 1 cm regionsof distal, medial and proximal colon were dissected, washed and bisectedfor colon culture with 0-80 ng/ml IL-6 in complete RPMI media. After 4hours of culture, colon pieces were harvested and processed for qRT-PCR,as described above.

Intestinal qRT-PCR, Western Blots, and Cytokine Profiles

1 cm regions of the distal, medial and proximal colon and smallintestine were washed in HBSS and either a) homogenized in ice-coldTrizol for RNA isolation and reverse transcription according to Hsiaoand Patterson, 2011, or b) homogenized in Tissue Extraction Reagent I(Invitrogen) containing EDTA-free protease inhibitors (Roche) forprotein assays. For SYBR green qRT-PCR, validated primer sets wereobtained from Primerbank (Harvard). For cytokine profiling, mouse20-plex cytokine arrays (Invitrogen) were run on the Luminex FLEXMAP 3Dplatform by the Clinical Immunobiology Correlative Studies Laboratory atthe City of Hope (Duarte, Calif.). Western blots were conductedaccording to standard methods and probed with rabbit anti-claudin 8 orrabbit anti-claudin 15 (Invitrogen) at 1:100 dilution.

Microbial DNA Extraction, 16S rRNA Gene Amplification and Pyrosequencing

Bacterial genomic DNA was extracted from mouse fecal pellets using theMoBio PowerSoil Kit following protocols benchmarked as part of the NIHHuman Microbiome Project. The V3-V5 regions of the 16S rRNA gene werePCR amplified using individually barcoded universal primers containinglinker sequences for 454-pyrosequencing. Sequencing was performed at theHuman Genome Sequencing Center at Baylor College of Medicine using amultiplexed 454-Titanium pyrosequencer.

16S rRNA Gene Sequence Analysis

FASTA and quality files were obtained from the Alkek Center forMetagenomics and Microbiome Research at the Baylor College of Medicineand quality filtered. Sequences <200 bp and >1000 bp, and sequencescontaining any primer mismatches, barcode mismatches, ambiguous bases,homopolymer runs exceeding six bases, or an average quality score ofbelow 30 were discarded. Quality filtered sequences were then analyzedusing the QIIME 1.6 software package (Caporaso et al., 2010b). Sequenceswere then checked for chimeras and clustered to operational taxonomicunits (OTUs) using the USearch pipeline (Edgar, 2010; Edgar et al.,2011) with a sequence similarity index of 97%. OTUs were subsequentlyassigned taxonomic classification using the basic local alignment searchtool (BLAST) classifier (Altschul et al, 1990), based on the smallsubunit non-redundant reference database release 111 (Quest et al, 2013)with 0.001 maximum e-value. These taxonomies were then used to generatetaxonomic summaries of all OTUs at different taxonomic levels. Fortree-based alpha- and beta diversity analyses, representative sequencesfor each OTU were aligned using PyNAST (Caporaso et al., 2010a) and aphylogenetic tree was constructed based on this alignment using FastTree(Price et al., 2009). Alpha diversity estimates (by Observed Species andFaith's phylogenetic diversity [PD]; (Faith, 1992)) and evenness (bySimpson's evenness and Gini Coefficient; (Wittebolle et al., 2009)) werecalculated and compared between groups using a nonparametric test basedon 100 iterations using a rarefaction of 2082 sequences from eachsample. For beta diversity, even sampling of 2160 sequences per samplewas used, and calculated using weighted and unweighted UniFrac (Lozuponeand Knight, 2005). Beta Diversity was compared in a pairwise fashion(Saline (S) vs Poly(I:C) (P), Poly(I:C) (P) vs Poly(I:C)+B. fragilistreatment (P+BF)) using the Analysis of Similarity (ANOSIM; Fierer et al2010) with 999 permutations to determine statistical significance.

Identification of Differences in Specific OTUs

Key OTUs, that discriminate between Saline and Poly(I:C) treatmentgroups, and between Poly(I:C) and Poly(I:C)+B. fragilis treatmentgroups, were identified using an unbiased method from OTU tables,generated by QIIME, using three complimentary analyses: (1) Metastatscomparison (White et al., 2009), (2) the Random Forests algorithm, firstunder QIIME (Knights et al., 2011) and subsequently coupled with Borutafeature selection, in the Genboree microbiome toolset (Riehle et al.,2012), and (3) the Galaxy platform-based LDA Effect Size analysis(LEfSe; (Segata et al., 2011)). Only OTUs that differ significantlybetween treatment groups were candidates for further analyses (p<0.05for (1) and (3), and >0.0001 mean decrease in accuracy for RandomForests and subsequent identification by the Boruta algorithm).Metastats analyses were done using the online interface(http://metastats.cbcb.umd.edu) with QIIME-generated OTU tables of anytwo treatment groups. The Random Forests algorithm was used to identifydiscriminatory OTUs in the QIIME software package (Breiman, 2001;Knights et al., 2011), comparing two treatment groups at a time, basedon 1000 trees and a 10-fold cross-validation, and was further validatedand coupled with the Boruta feature selection algorithm, as implementedin the Genboree Microbiome toolset (Kursa and Rudnicki, 2010; Riehle etal., 2012). Only those OTUs that were confirmed by the Boruta algorithmwere defined as discriminatory. The ratio between observed andcalculated error rates was used as a measure of confidence for RandomForests Analyses: this ratio was 5.0 for saline vs. poly(I:C) (with anestimated error of 0.1±0.21) and 2.86 for poly(I:C) vs. poly(I:C)+B.fragilis (with an estimated error of 0.23±0.22). In order to overcomeany mislabeling by any one of the three methods only OTUs that wereidentified by at least two of the three above methods were defined asdiscriminatory. For the analyses in FIG. 1, OTUs that were significantlyaltered by MIA were identified by comparing the saline vs. poly(I:C)groups. For the analyses in FIG. 6, the poly(I:C) vs. poly(I:C)+B.fragilis groups were compared, and only report only those OTUs that havealso been identified by the analyses in FIG. 1.

Key OTUs were than aligned using the SINA aligner(http://www.arb-silva.de/aligner/; Pruesse et al., 2012), compared tothe SILVA reference database release 111 (Quast et al., 2013) using Arb(Ludwig et al., 2004) and visualized using FigTree(http://tree.bio.ed.ac.uk/software/figtree/). Heat maps of key OTUs weregenerated by extracting their relative abundance from the OTU table.These data were then normalized (so that the sum of squares of allvalues in a row or column equals one), first by OTU and subsequently bysample, and clustered by correlation using Cluster 3.0 (de Hoon et al.,2004). Finally, abundance data was visualized using Java TreeView(Saldanha, 2004).

B. fragilis Colonization Assay

Fecal samples were sterilely collected from MIA and control offspring at1, 2 and 3 weeks after the start of treatment with B. fragilis orvehicle. Germ-free mice were treated with B. fragilis as described aboveto serve as positive controls. DNA was isolated fecal samples using theQJAamp DNA Stool Mini Kit (Qiagen). 50 ng DNA was used for qPCR with B.fragilis-specific, 5′ TGATTCCGCATGGTTTCATT 3′ (SEQ ID NO: 1) and 5′CGACCCATAGAGCCTTCATC 3′ (SEQ ID NO: 2), and universal 16S primers 5′ACTCCTACGGGAGGCAGCAGT 3′ (SEQ ID NO: 3) and 5′ ATTACCGCGGCTGCTGGC 3′(SEQ ID NO: 4) according to Odamaki et al., 2008.

Behavioral Testing

Adult MIA and control offspring were behaviorally tested as described inHsiao et al., 2012 and Malkova et al., 2012. Mice were tested beginningat 6 weeks of age for pre-pulse inhibition, open field exploration,marble burying, social interaction and adult ultrasonic vocalizations,in that order, with at least 5 days between behavioral tests. Behavioraldata for B. fragilis treatment and control groups (FIG. 10) representcumulative results collected from multiple litters of 3-5 independentcohorts of mice for PPI and open field tests, 2-4 cohorts for marbleburying, 2 cohorts for adult male ultrasonic vocalization and 1 cohortfor social interaction. Discrepancies in sample size across behavioraltests reflect differences in when during our experimental study aparticular test was implemented.

Pre-Pulse Inhibition.

PPI tests are used as a measure of sensorimotor gating and wereconducted and analyzed according to the procedure described in Geyer andSwerdlow, 2001 and Smith et al., 2007. Briefly, mice were acclimated tothe testing chambers of the SR-LAB startle response system (San DiegoInstruments) for 5 minutes, presented with six 120 db pulses of whitenoise (startle stimulus) and then subjected to 14 randomized blocks ofeither no startle, startle stimulus only, 5 db prepulse with startle or15 db prepulse with startle. The startle response was recorded by apliezo-electric sensor, and the percent PPI is defined as: [((startlestimulus only−5 or 15 db prepulse with startle)/startle stimulusonly)*100].

Open Field Exploration.

The open field test is widely used to measure anxiety-like and locomotorbehavior in rodents. Mice were placed in 50×50 cm white Plexiglas boxesfor 10 minutes. An overhead video camera recorded the session, andEthovision software (Noldus) was used to analyze the distance traveled,and the number of entries and duration of time spent in the center arena(central 17 cm square).

Marble Burying.

Marble burying is an elicited repetitive behavior in rodents analogousto those observed in autistic individuals (Silverman et al., 2010b).This test was conducted and analyzed according to methods described inThomas et al., 2009 and Malkova et al., 2012. Mice were habituated for10 minutes to a novel testing cage containing a 4 cm layer of chippedcedar wood bedding and then transferred to a new housing cage. 18 glassmarbles (15 mm diameter) were aligned equidistantly 6×3 in the testingcage. Mice were returned to the testing cage and the number of marblesburied in 10 minutes was recorded.

Sociability and Social Preference.

Social interaction tests were conducted and analyzed according tomethods adopted from Sankoorikal et al., 2006 and Yang et al., 2011.Briefly, testing mice were habituated for 10 minutes to a 40×60 cmPlexiglas three-chambered apparatus containing clear interactioncylinders in each of the side chambers. Sociability was tested in thefollowing 10 minute session, where the testing mouse was given theopportunity to explore a novel same-sex, age-matched mouse in oneinteraction cylinder (social object) versus a novel toy (green stickyball) in the other interaction cylinder of the opposite chamber. Socialpreference was tested in the final 10 minute session, where the testingmouse was given the opportunity to explore a now familiar mouse(stimulus mouse from the previous sociability session) versus a novelunfamiliar same-sex, age-matched mouse. In each session, the trajectoryof the testing mouse was tracked with Ethovision software (Noldus).Sociability data is presented as preference for the mouse over the toy:percent of time in the social chamber—percent of time in the nonsocialchamber, and social preference data is presented as preference for theunfamiliar mouse over the familiar mouse: percent of time in theunfamiliar mouse chamber—percent of time in the familiar mouse chamber.Similar indexes were measured for chamber entries, and entries into andduration spent in the contact zone (7×7 cm square surrounding theinteraction cylinder).

Adult Ultrasonic Vocalizations.

Male mice produce USVs in response to female mice as an important formof communication (Portfors, 2007). Adult male USV production in responseto novel female exposure was measured according to methods described inGrimsley et al., 2011; Scattoni et al., 2011; and Silverman et al.,2010a. Adult males were single-housed one week before testing andexposed for 20 minutes to an unfamiliar adult female mouse each daystarting four days prior to testing in order to provide a standardizedhistory of sexual experience and to adjust for differences in socialdominance. On testing day, mice were habituated to a novel cage for 10minutes before exposure to a novel age-matched female. USVs wererecorded for 3 minutes using the UltraSoundGate microphone and audiosystem (Avisoft Bioacoustics). Recordings were analyzed using Avisoft'sSASLab Pro software after fast Fourier transformation at 512 FFT-lengthand detection by a threshold-based algorithm with 5 ms hold time. Datapresented reflect duration and number of calls produced in the 3 minutesession.

Metabolomics Screening

Sera were collected by cardiac puncture from behaviorally validatedadult mice. Samples were extracted and analyzed on GC/MS, LC/MS andLC/MS/MS platforms by Metabolon, Inc. Protein fractions were removed byserial extractions with organic aqueous solvents, concentrated using aTurboVap system (Zymark) and vacuum dried. For LC/MS and LC/MS/MS,samples were reconstituted in acidic or basic LC-compatible solventscontaining >11 injection standards and run on a Waters ACQUITY UPLC andThermo-Finnigan LTQ mass spectrometer, with a linear ion-trap front-endand a Fourier transform ion cyclotron resonance mass spectrometerback-end. For GC/MS, samples were derivatized under dried nitrogen usingbistrimethyl-silyl-trifluoroacetamide and analyzed on a Thermo-FinniganTrace DSQ fast-scanning single-quadrupole mass spectrometer usingelectron impact ionization. Chemical entities were identified bycomparison to metabolomic library entries of purified standards.Following log transformation and imputation with minimum observed valuesfor each compound, data were analyzed using two-way ANOVA withcontrasts.

4EPS Synthesis and Detection

Potassium 4-ethylphenylsulfate was prepared using a modification of aprocedure reported for the synthesis of aryl sulfates in Burlingham etal., 2003 and Grimes, 1959 (FIG. 15A). 4-ethylphenol (Sigma-Aldrich,5.00 g, 40.9 mmol) was treated with sulfur trioxide-pyridine complex(Sigma-Aldrich, 5.92 g, 37.2 mmol) in refluxing benzene (20 ml, dried bypassing through an activated alumina column). After 3.5 hours, theresulting solution was cooled to room temperature, at which point theproduct crystallized. Isolation by filtration afforded 7.93 g of crudepyridinium 4-ethylphenylsulfate as a white crystalline solid. 1.00 g ofthis material was dissolved in 10 mL of 3% triethylamine in acetonitrileand filtered through a plug of silica gel (Silicycle, particle size32-63 μm), eluting with 3% triethylamine in acetonitrile. The filtratewas then concentrated, and the resulting residue was dissolved in 20 mLof deionized water and eluted through a column of Dowex 50WX8 ionexchange resin (K⁺ form), rinsing with 20 mL of deionized water. The ionexchange process was repeated once more, and the resulting solutionconcentrated under vacuum to afford 618 mg (55% overall yield) ofpotassium 4-ethylphenylsulfate as a white powder (FIG. 15A).

¹H and ¹³C NMR spectra of authentic potassium 4-ethylphenylsulfate wererecorded on a Varian Inova 500 spectrometer and are reported relative tointernal DMSO-d₅ (¹H, δ=2.50; ¹³C, δ=39.52). A high-resolution massspectrum (HRMS) was acquired using an Agilent 6200 Series TOF with anAgilent G1978A Multimode source in mixed ionization mode (electrosprayionization (ESI) and atmospheric pressure chemical ionization (APCI)).Spectroscopic data for potassium 4-ethylphenylsulfate are as follows: ¹HNMR (DMSO-d₆, 500 MHz) δ 7.11-7.04 (m, 4H), 2.54 (q, J=7.6 Hz, 2H), 1.15(t, J=7.6 Hz, 3H); ¹³C NMR (DMSO-d₆, 126 MHz) δ 151.4, 138.3, 127.9,120.6, 27.5, 16.0; HRMS (Multimode-ESI/APCI) calculated for C₈H₉O₄S[M−K]⁻ 201.0227, found 201.0225.

Authentic 4EPS and serum samples were analyzed by LC/MS using an Agilent110 Series HPLC system equipped with a photodiode array detector andinterfaced to a model G1946C single quadrupole expectospray massspectrometer. HPLC separations were obtained at 25° C. using an AgilentZorbax XDB-C18 column (4.6 mm×50 mm×5 um particle size). The 4EPS ionwas detected using selected ion monitoring for ions of m/z 200.9 anddwell time of 580 ms/ion, with the electrospray capillary set at 3 kV.Authentic potassium 4EPS was found to possess a retention time of 6.2minutes when eluted in 0.05% trifluoroacetic acid and acetonitrile,using a 10-minute linear gradient from 0-50% acetonitrile. Forquantification of 4EPS in mouse sera, a dose-response curve wasconstructed by plotting the total ion count peak area for knownconcentrations of authentic potassium 4EPS against the analyteconcentration (R̂2=0.9998; FIG. 15B). Mouse serum samples were dilutedfour-fold with acetonitrile and centrifuged at 10,000 g at 4° C. for 3minutes. 10 ul of supernatant was injected directly into the HPLCsystem.

4EPS Sufficiency Experiments

Wildtype mice were injected i.p. with saline or 30 mg/kg 4EPS potassiumsalt daily from 3 to 6 weeks of age. A dose-response curve was generatedby measuring serum 4EPS levels at various times after i.p. injection of30 mg/kg 4EPS (FIG. 15C). Mice were behaviorally tested as describedabove from 6 to 9 weeks of age.

Statistical Analysis

Statistical analysis was performed using Prism software (Graphpad). Datawere assessed for normal distribution and plotted in the figures asmean±SEM. Differences between two treatment groups (i.e. control versus4EPS) were assessed using two-tailed, unpaired Student t test withWelch's correction. Differences among multiple groups (saline versuspoly(I:C) versus poly(I:C)+B. fragilis/B. thetaiotaomicron) wereassessed using one-way ANOVA with Bonferroni post hoc test. Two-wayrepeated measures ANOVA with Bonferroni post hoc test was used foranalysis of PPI and CD4+ T-cell stimulation data. Two-way ANOVA withcontrasts was used for analysis of the metabolite data. Sample sizesdenote the number of individual mice per treatment group, given theindividual randomization design of the study (Lazic, 2013). Significantdifferences emerging from the above tests are indicated in the figuresby *p<0.05, **p<0.01, ***p<0.001. Notable near-significant differences(0.5<p<0.1) are indicated in the figures. Notable non-significant (andnon-near significant) differences are indicated in the figures by“n.s.”.

Example 1 Offspring of Immune-Activated Mothers Exhibit GI Symptoms ofHuman ASD

Adult MIA offspring, which exhibit cardinal behavioral andneuropathological symptoms of ASD (Malkova et al., 2012), were alsofound to display a significant deficit in intestinal barrier integrity,as reflected by increased translocation of orally administeredFITC-dextran across the intestinal epithelial layer and into thecirculation (FIG. 1A, left panel). This MIA-associated increase inintestinal permeability is similar to what's seen in mice treated withdextran sodium sulfate (DSS), a chemical used to induce experimentalcolitis (FIG. 1A, left panel) (Wirtz et al., 2007). Deficits inintestinal integrity were detectable in 3-week-old MIA offspring (FIG.1A, right panel), indicating that the abnormality was established duringearly life. To assess the molecular basis for increased intestinalpermeability in MIA offspring, colons of MIA offspring were examined forthe tight junction components ZO-1 (TJP1), ZO-2 (TJP2), ZO-3 (TJP3),occludin and claudins (CLDN) 1, 2, 3, 4, 7, 8, 12, 13 and 15 (Holmes etal., 2006). Consistent with the leaky gut phenotype found in subsets ofASD children displaying GI abnormalities, colons from adult MIAoffspring exhibited decreased expression of transcripts for ZO-1, ZO-2,occludin and claudin 8, and increased expression of claudin 15 mRNA(FIG. 1B). Deficient expression of ZO-1 is also observed in smallintestines of adult MIA offspring (FIG. 2A), demonstrating a widespreaddefect in intestinal barrier integrity.

Increased permeability is observed in several intestinal diseases, aswell as subsets of ASD, and is commonly associated with signs ofinflammation (Hering et al., 2012; Turner, 2009; White, 2003). Inaddition to changes in expression of tight junction components, colonsfrom adult MIA offspring were found to display increased levels ofinterleukin-6 (IL-6) mRNA and protein (FIGS. 1C and 1D) and decreasedlevels of the cytokines/chemokines IL-12p40/p70, IP-10, MIG and MIP-1α(FIG. 1D). Small intestines from MIA offspring also exhibit alteredcytokine/chemokine profiles (FIG. 2C). Changes in intestinal cytokineswere not accompanied by overt GI pathology, as assessed by histologicalexamination of gross epithelial morphology from hematoxylin- andeosin-stained sections. Consistent with the alterations inimmune-related signaling factors, however, mesenteric lymph nodes andspleens from adult MIA offspring were found to contain decreased levelsof regulatory T cells and hyper-responsive production of IL-6 and IL-17by CD4+ T helper cells, suggestive of a pro-inflammatory phenotype (FIG.3A-D) (Hsiao et al., 2012). Similar findings supporting enteric immuneactivation are seen in subsets of ASD individuals (Onore et al., 2012).

In view of the foregoing, this examples shows that adult offspring ofimmune-activated mothers exhibit increased gut permeability and abnormalintestinal cytokine profiles, recapitulating ASD-related GI symptoms ina mouse model.

Example 2 MIA Offspring Display Dysbiosis of the Gut Microbiota

The potential link between disruption of the normal gut microbiota andGI dysfunction in an ASD mouse model was examined in this example.

To evaluate whether MIA induces microbiota alterations, the fecalbacterial population was surveyed by 16S rRNA gene sequencing of samplesisolated from adult offspring of mothers treated with poly(I:C) orsaline. Alpha diversity, i.e., species richness and evenness, did notdiffer significantly between control and MIA offspring, as measured byFaith's phylogenetic diversity (PD) index, and number of ObservedSpecies (p=1.0000 and 0.2790, respectively) and the Gini coefficient andSimpson evenness index (p=0.5430 and p=0.2610, respectively; FIGS. 4Aand 4B). In contrast, unweighted UniFrac analysis, which measures thedegree of phylogenetic similarity between microbial communities, revealsa strong effect of MIA on the gut microbiota of adult offspring (FIG.5A-E). MIA samples cluster distinctly from controls by principalcoordinate analysis (PCoA; ANOSIM R=0.2829, p=0.0030), indicating robustchanges in the membership of gut bacteria from MIA offspring compared tocontrols (FIG. 5A). The effect of MIA on altering the composition of thegut microbiota is further evident when sequences from the classesClostridia and Bacteroidia, which account for approximately 90.1% of thetotal reads in our survey (46,484 reads out of 51,586 in the S and Pgroups), were exclusively examined by PCoA (R=0.2331, p=0.0070; FIG.5B), but not when Clostridia and Bacteroidia sequences were specificallyexcluded from PCoA of all other bacterial classes (R=0.1051, p=0.0700;FIG. 5C). This indicates that changes in the diversity of Clostridia andBacteroidia operational taxonomic units (OTUs) are the primary driversof gut microbiota differences between MIA offspring and controls.

67 OTUs out of the 1474 OTUs detected across any of the samplesdiscriminate between treatment groups, including those assigned to thebacterial families Lachnospiraceae, Ruminococcaceae,Erysipelotrichaceae, Alcaligenaceae, Porphyromonadaceae, Prevotellaceae,and Rikenellaceae, and unclassified Bacteroidales (FIG. 5D). Of these 67discriminatory OTUs, 19 are more abundant in control samples and 48 aremore abundant in MIA samples. Consistent with the PCoA results (FIGS.5A-C), the majority of OTUs that discriminate MIA offspring fromcontrols are assigned to the classes Bacteroidia (45 of 67 OTUs; 67.2%)and Clostridia (17 of 67 OTUs; 25.4%), whereas the few remainingdiscriminatory OTUs belong to Proteobacteria (3 OTUs; 4.5%) and otherclasses (Tenericutes and unclassified, 1 OTU each; 3.0%). Interestingly,Porphyromonadaceae, Prevotellaceae, and many unclassified Bacteriodales(36 of the 45 discriminatory Bacteroidial OTUS; 80%), andLachnospiriceae (8 of the 14 discriminatory Clostridial OTUs; 57%) weremore abundant in MIA offspring. Conversely, Ruminococcaceae (2 OTUs),Erysipelotrichaceae (2 OTUs), and the beta Proteobacteria familyAlcaligenaceae (2 OTUs) were more abundant in control offspring (FIG.5D). These data indicate that specific Lachnospiraceae, along with otherBacteroidial species, play an important role in MIA pathogenesis, whileother taxa may have a protective role. Importantly, there is nosignificant difference in the overall relative abundance of Clostridia(13.63±2.54% vs 14.44±2.84% mean±SEM; Student's t-test p=0.8340) andBacteroidia (76.25±3.22% vs 76.22±3.46% mean±SEM; Student's t-testp=0.9943) between MIA offspring and controls (FIG. 5E, left panel),indicating that alterations in the membership of rare OTUs drive majorchanges in the gut microbiota between experimental groups.

Differences in taxonomic diversity was also seen in less prominentbacterial classes, with MIA offspring displaying significantly decreasedrelative abundance of Erysipelotrichi (0.15±0.03% v.s. 0.74±0.25%mean±SEM; Student's t-test p-value=0.0334) compared to controls (FIG.5E, right panel). Overall, MIA was found to lead to dysbiosis of the gutmicrobiota, driven primarily by alterations in specific OTUs of thebacterial classes Clostridia and Bacteroidia. Changes in OTUs classifiedas Lachnospiraceae and Ruminococcaceae of the order Clostridialesparallel reports of increased Clostridium species in the feces ofsubjects with ASD (Finegold et al., 2012). Altogether, modeling MIA as aprimary autism risk factor in mice induces not only behavioral andneuropathological features of ASD (Boksa, 2010), but also GI symptomsanalogous to those described in subsets of ASD individuals. The datapresented herein shows that MIA can be used as a model for human ASDwith comorbid GI issues.

Example 3 B. fragilis Treatment Improves Gut Barrier Integrity in MIAOffspring

Gut microbes play an important role in the development, maintenance andrepair of the intestinal epithelium (Sharma et al., 2010; Turner, 2009).To determine whether targeting the gut microbiota could impact thedevelopment or persistence of MIA-associated GI abnormalities, offspringwas treated with the human commensal bacterium B. fragilis at weaning,and then tested for GI abnormalities at 8 weeks of age. Remarkably, B.fragilis treatment corrected intestinal permeability in MIA offspring(FIG. 6A). In addition, B. fragilis treatment ameliorated MIA-associatedchanges in gene expression of CLDNs 8 and 15, but had no significanteffect on expression levels of TJP1, TJP2 or OCLN mRNA (FIG. 6B).Similar changes are observed in protein levels of claudin 8 and 15 inthe colon, with restoration by B. fragilis treatment (FIGS. 6C-D). Nosuch effects of B. fragilis on tight junction expression are observed insmall intestines from MIA offspring (FIG. 2B), consistent with the factthat Bacteroides species are predominantly found in the colon. Also, thepresence of GI defects prior to probiotic administration (FIG. 1A, rightpanel) suggests that B. fragilis can treat ASD-related pathology in MIAoffspring.

B. fragilis treatment also restored MIA-associated increases in colonIL-6 mRNA and protein levels to those found in control mice (FIGS.6E-F). Levels of other cytokines were altered in both colons and smallintestines of MIA offspring (FIGS. 1D and 2C), but these were notaffected by B. fragilis treatment, revealing specificity for IL-6. Thisfinding is consistent with a critical role for IL-6 in the MIA model(Smith et al., 2007). Altered intestinal cytokine profiles may form thebasis for the increased intestinal permeability observed in MIAoffspring, as several cytokines including IL-6 are reported to modulatetight junctions and regulate intestinal barrier integrity (Suzuki etal., 2011; Turner, 2009). It was further found that recombinant IL-6treatment can modulate colon levels of both claudin 8 and claudin 15 invivo and in in vitro colon organ cultures (FIG. 7A-C), suggesting thatB. fragilis-mediated restoration of colonic IL-6 levels could underlieits effects on gut permeability. Collectively, these findingsdemonstrate that B. fragilis treatment of MIA offspring reverses defectsin GI barrier integrity, and corrects alterations in tight junction andcytokine expression.

Example 4 B. fragilis Treatment Restores Microbiota Changes in MIAOffspring

In addition to ameliorating GI physiology in MIA offspring, B. fragilistreatment induces long-term effects on the composition of the intestinalmicrobiota. No significant differences were observed at the global levelby PCoA (ANOSIM R=0.0060 p=0.4470) or in microbiota richness (PD:p=0.2980, Observed Species: p=0.5440) and evenness (Gini: p=0.6110,Simpson Evenness: p=0.5600; FIGS. 8A, 4A-B). However, corrective effectsof B. fragilis treatment were apparent upon evaluating specific key OTUsthat discriminate adult MIA offspring from controls (FIG. 8B).Specifically, MIA offspring treated with B. fragilis displayed completerestoration in the relative abundance of 6 out of the 67 OTUsdiscriminate MIA from control offspring (28 other OTUs, not identifiedas discriminatory between MIA and control offspring, could discriminatebetween MIA offspring and those that have been treated with B.fragilis). These 6 OTUs are taxonomically assigned as unclassifiedBacteroidia and Clostridia of the family Lachnospiraceae (FIG. 8B).Notably, these alterations occurred in the absence of persistentcolonization of B. fragilis, which remains undetectable in fecal andcecal samples isolated from treated MIA offspring, as assessed byquantitative real-time PCR (FIG. 9A-B). Interestingly, 4 of the 10Lachnospiraceae elevated in MIA offspring were corrected by B. fragilistreatment (FIGS. 5D and 8A-C). In addition, B. fragilis treatmentrestored the relative abundance of 2 Bacteroidia OTUs to levels observedin controls (FIG. 8B). Phylogenetic reconstruction of the 6 OTUs thatwere altered by MIA and restored by B. fragilis treatment reveals thatthe two Bacteroidia OTUs cluster together into a monophyletic group(FIG. 8D). In addition, the Lachnospiraceae OTUs that were significantlyaltered by MIA and corrected by B. fragilis cluster into 2 separatemonophyletic groups (FIG. 8D). These results indicate that, althoughtreatment of MIA offspring with B. fragilis may not lead to persistentcolonization of B. fragilis itself, it can correct the relativeabundance of specific groups of related microbes of the Lachnospiraceaefamily as well as unclassified Bacteriodales.

Altogether, this example demonstrates that treatment of MIA offspringwith B. fragilis can ameliorate particular changes involved inMIA-associated dysbiosis of the commensal microbiota and correct GIabnormalities similar to those observed in subsets of autisticindividuals.

Example 5 B. fragilis Treatment Corrects ASD-Related BehavioralAbnormalities

To explore the potential impact of GI dysfunction on core ASD behavioralabnormalities, the question whether B. fragilis treatment impactsASD-related behaviors in MIA offspring was investigated.

Adult MIA offspring were found to display cardinal behavioral featuresof ASD in a variety of behavioral assays. Open field explorationinvolves mapping an animal's movement in an open arena to measure oflocomotion and anxiety (Bailey and Crawley, 2009). MIA offspringdisplayed decreased entries and time spent in the center of the arena,but no difference in the total distance traveled, which is indicative ofanxiety-like behavior (FIG. 10A; compare saline (S) to poly(I:C) (P)).The pre-pulse inhibition (PPI) task measures the ability of an animal toinhibit its startle in response to an acoustic tone (“pulse”) when it ispreceded by a lower-intensity stimulus (“pre-pulse”). Deficiencies inPPI are a measure of impaired sensorimotor gating, and are observed inseveral neurodevelopmental disorders, including autism (Perry et al.,2007). MIA offspring exhibited decreased PPI in response to 5 or 15 dbpre-pulses (FIG. 10B). The marble burying test measures the propensityof mice to engage repetitively in a natural digging behavior that is notconfounded by anxiety (Thomas et al., 2009). MIA offspring displayedincreased stereotyped marble burying compared to controls (FIG. 10C),which models repetitive behavior as a core ASD symptom. Ultrasonicvocalizations are used to measure communication by mice, given thatseveral types of calls are produced and used in structured motifs thatvary across different social paradigms (Grimsley et al., 2011; Scattoniet al., 2011; Silverman et al., 2010b). MIA offspring exhibitedASD-related deficits in communication, as indicated by reduced numberand duration of ultrasonic vocalizations produced in response to asocial encounter (FIG. 10D). Finally, the three-chamber social test isused to measure ASD-related impairments in social interaction (Silvermanet al., 2010a). Sociability is exemplified by a mouse's preference tointeract with a novel mouse over a novel object, while social novelty(social preference) is characterized by preference to interact with anunfamiliar versus a familiar mouse. MIA offspring exhibited deficits inboth sociability and social preference (FIG. 10E-F). Altogether, therebehavioral assays evaluate the cardinal diagnostic symptoms of ASD, inaddition to ASD-associated anxiety and deficient sensorimotor gating,have been broadly used to phenotype ASD mouse models (Han et al., 2012;Novarino et al., 2012; Schmeisser et al., 2012; Silverman et al., 2010a;Tabuchi et al., 2007; Tsai et al., 2012; Won et al., 2012).

Remarkably, oral treatment with B. fragilis ameliorated many of theseASD-related behavioral abnormalities. B. fragilis-treated MIA offspringdid not exhibit anxiety-like behavior in the open field (FIG. 10A;compare poly(I:C) (P) to poly(I:C)+B. fragilis (P+BF)), as shown byrestoration in the number of center entries and duration of time spentin the center of the open field. B. fragilis improved sensorimotorgating in MIA offspring, as indicated by increased combined PPI inresponse to 5 and 15 db pre-pulses (FIG. 10B), with no significanteffect on the intensity of startle to the acoustic stimulus (data notshown). B. fragilis-treated MIA offspring also exhibited decreasedlevels of stereotyped marble burying and restored communicativebehavior, as illustrated by increased number and duration of ultrasonicvocalizations (FIG. 10C-D). Interestingly, B. fragilis treatment raisedthe duration per call produced by MIA offspring to levels that exceedthat observed in saline controls (FIG. 10D), suggesting that despitenormalization of the propensity to communicate (no difference comparedto controls in the number of calls produced), there is a qualitativedifference in the types of calls generated with enrichment of longersyllables.

Although B. fragilis-treated MIA offspring exhibited improvedcommunicative, repetitive, anxiety-like and sensorimotor behavior, theyretain deficits in sociability and social preference (FIG. 10E).Interestingly, this parallels the inability to improve social behaviorby administration of risperidone to ASD individuals (Canitano andScandurra, 2008) and to CNTNAP2 knockout mice, a genetic mouse model forASD (Penagarikano et al., 2011). These data indicate that there arefundamental differences in the circuitry or circuit plasticity governingsocial behavior as compared to the other behaviors, and that B. fragilistreatment modulates specific brain circuits during amelioration ofASD-related behavioral defects in MIA offspring.

In addition, behavioral improvement in response to B. fragilis treatmentwas not associated with changes in systemic immunity in MIA offspring(FIGS. 3A-C) and was not dependent on polysaccharide A (PSA), a moleculepreviously identified to confer immunomodulatory effects by B. fragilis(FIG. 3E) (Mazmanian et al., 2008; Ochoa-Reparaz et al., 2010; Round andMazmanian, 2010). Furthermore, amelioration of behavior is not specificto B. fragilis, as similar treatment with Bacteroides thetaiotaomicron,also significantly improves anxiety-like, repetitive and communicativebehavior in MIA offspring (FIGS. 11A-D). This is consistent with ourfinding that B. fragilis treatment does not lead to persistentcolonization of B. fragilis in the GI tract (FIGS. 9A-B), and may beacting by causing long-term shifts in the resident microbiota (see FIG.4).

Example 6 The Serum Metabolome is Modulated by MIA and B. fragilisTreatment

Metabolomic studies have shown that gut microbial products are found inmany extra-intestinal tissues, and molecules derived from the microbiotamay influence metabolic, immunologic and behavioral phenotypes in miceand humans (Bercik et al., 2011; Blumberg and Powrie, 2012; Hooper etal., 2012; MacFabe, 2012; Matsumoto et al., 2012; Nicholson et al.,2012). In this example, potential was examined.

Gas chromatography/liquid chromatography with mass spectrometry(GC/LC-MS)-based metabolomic profiling was used to identifyMIA-associated changes in serum metabolites. 2,400 metabolites wereassayed and of these, 322 metabolites, spanning amino acid (94), peptide(15), carbohydrate (22), energy (10), lipid (128), nucleotide (23),xenobiotic (19) and cofactor and vitamin (11) super pathways weredetected in sera from adult mice (Table 4). Interestingly, MIA leads tostatistically significant alterations in 8% of all serum metabolitesdetected (Table 3). Furthermore, postnatal B. fragilis treatment has asignificant effect on the serum metabolome, altering 34% of allmetabolites detected (Table 4 and FIG. 12).

TABLE 3 Serum Metabolites Altered in Adult Saline versus Poly(I:C)Offspring Super Fold p- Pathway Sub-pathway Metabolite Change valueAmino acid Glycine, serine N-acetylserine 0.73 0.0354 and threoninemetabolism Amino acid Alanine and beta-alanine 0.46 0.0500 aspartatemetabolism Amino acid Glutamate glutamine 1.2 0.0173 metabolism Aminoacid Histidine transurocanate 1.71 0.0240 metabolism Amino acidHistidine imidazole propionate 1.35 0.0161 metabolism Amino acidPhenylalanine phenylacetylglycine 0.71 0.0821 and tyrosine metabolismAmino acid Phenylalanine phenol sulfate 0.68 0.0092 and tyrosinemetabolism Amino acid Tryptophan indolepyruvate 1.57 0.0240 metabolismAmino acid Tryptophan serotonin 1.15 0.0804 metabolism Amino acidValine, leucine 3-methyl-2-oxovalerate 0.75 0.0152 and isoleucinemetabolism Amino acid Valine, leucine 4-methyl-2-oxopentaoate 0.7 0.0072and isoleucine metabolism Amino acid Cysteine, cysteine 0.73 0.0582methionine, SAM, taurine metabolism Amino acid Urea cycle; arginine 0.870.0761 arginine-, proline-, metabolism Amino acid Urea cycle; ornithine0.68 0.0956 arginine-, proline-, metabolism Amino acid Polyamine5-methylthioadenosine 1.34 0.0425 metabolism Peptide Dipeptideglycylvaline 0.48 0.0077 Peptide Fibrinogen TDTEDKGEFLSEGGGVR 1.8 0.0567cleavage peptide Carbohydrate Glycolysis, 3-phosphoglycerate 0.51 0.0265gluconeogenesis, pyruvate metabolism Carbohydrate Glycolysis,phosphoenolpyruvate 0.56 0.0344 gluconeogenesis, pyruvate metabolismCarbohydrate Nucleotide ribose 1.44 0.0499 sugars, pentose metabolismCarbohydrate Nucleotide xylose 1.34 0.0827 sugars, pentose metabolismLipid Essential fatty docosapentaenoate (n3 DPA; 22:5n3) 0.75 0.0988acid Lipid Essential fatty docosapentaenoate (n6 DPA; 22:5n6) 0.830.0970 acid Lipid Essential fatty docosahexaenoate (DHA; 22:6n3) 0.80.0965 acid Lipid Long chain fatty stearate 0.88 0.0491 acid Lipid Longchain fatty eicosenoate 0.61 0.0151 acid Lipid Long chain fattydihomo-linoleate (20:2n6) 0.79 0.0614 acid Lipid Long chain fattyadrenate 0.82 0.0923 acid Lipid Fatty acid, 13-HODE + 9-HODE 0.72 0.0489monohydroxy Lipid Fatty acid, octadecanedioate 0.83 0.0413 dicarboxylateLipid Eicosanoid 12-HETE 0.69 0.0152 Lipid Inositol myo-inositol 0.860.0817 metabolism Lipid Lysolipid 1-palmitoylglycerophosphoethanolamine0.81 0.0868 Lipid Lysolipid 1-oleoylglycerophosphoethanolamine 0.70.0169 Lipid Lysolipid 1-pentadecanoylglycerophosphocholine 1.43 0.0505Lipid Lysolipid 1-palmitoleoylglycerophosphocholine 1.49 0.0388 LipidLysolipid 1-stearoylglycerophosphoinositol 0.64 0.0059 Lipid Lysolipid1-palmitoylplasmenylethanolamine 0.73 0.0399 Cofactors and Hemoglobinand bilirubin (E,E) 2.68 0.0496 vitamins porphyrin metabolism Cofactorsand Pantothenate and pantothenate 1.33 0.0643 vitamins CoA metabolismCofactors and Benzoate 4-ethylphenylsulfate 46.39 0.0359 vitaminsmetabolism Cofactors and Chemical glycolate (hydroxyacetate) 1.17 0.0498vitamins Cofactors and Food ergothioneine 0.72 0.0688 vitaminscomponent/Plant Cofactors and Food equol sulfate 0.78 0.0315 vitaminscomponent/Plant Summary of notable changes (p < 0.10) in levels of serummetabolites in 10-week old offspring of poly(I:C)-injected mothersversus controls. Serum samples were extracted and analyzed by GC/LC-MSby Metabolon, Inc. Data were analyzed using two-way ANOVA withcontrasts. Additional details are provided in Experimental Procedures.

TABLE 4 Serum Metabolites Altered in Saline and Poly(I:C) Offspringafter B. fragilis Treatment Super I:C-Bfrag Pathway Sub PathwayBiochemical Name Platform CON sarcosine (N-Methylglycine) GC/MS 0.64Alanine and aspartate GC/MS 0.76 aspartate 3-ureidopropionate LC/MS pos0.64 metabolism Lysine glutarate (pentanedioate) GC/MS 0.78 metabolismtyrosine LC/MS pos 0.85 3-(4-hydroxyphenyl)lactate LC/MS neg 0.813-phenylpropionate (hydrocinnamate) LC/MS neg 0.60 serotonin (5HT) LC/MSpos 1.26 Valine, 3-methyl-2-oxobutyrate LC/MS neg 0.68 leucine and3-methyl-2-oxovalerate LC/MS neg 0.67 isoleucine4-methyl-2-oxopentanoate LC/MS neg 0.63 metabolism isobutyrylcarnitineLC/MS pos 0.68 2-methylbutyroylcarnitine LC/MS pos 0.66isovalerylcarnitine LC/MS pos 0.76 2-hydroxybutyrate (AHB) GC/MS 0.64Urea cycle; arginine LC/MS pos 0.86 arginine-, ornithine GC/MS 0.66proline-, metabolism Butanoate 2-aminobutyrate LC/MS pos 0.76 metabolismGuanidino 4-guanidinobutanoate LC/MS pos 0.65 and acetamido metabolism5-oxoproline LC/MS neg 0.80 Peptide Dipeptide glycylvaline LC/MS pos0.22 gamma-glutamyltryptophan LC/MS pos 0.77 FibrinogenTDTEDKGEFLSEGGGV* LC/MS pos 1.43 cleavage TDTEDKGEFLSEGGGVR* LC/MS pos3.46 peptide sorbitol GC/MS 0.63 pyruvate GC/MS 0.58 ribitol GC/MS 0.74ribose GC/MS 1.97 ribulose GC/MS 0.68 xylitol GC/MS 1.62 Energy Krebscycle citrate GC/MS 0.80 fumarate GC/MS 0.64 malate GC/MS 0.69 LipidEssential linoleate (18:2n6) LC/MS neg 0.64 fatty acid linolenate [alphaor gamma; (18:3n3 or 6)] LC/MS neg 0.62 dihomo-linolenate (20:3n3 or n6)LC/MS neg 0.69 docosapentaenoate (n3 DPA; 22:5n3) LC/MS neg 0.72docosapentaenoate (n6 DPA; 22:5n6) LC/MS neg 0.70 docosahexaenoate (DHA;22:6n3) LC/MS neg 0.77 heptanoate (7:0) LC/MS neg 0.81 pelargonate (9:0)LC/MS neg 0.81 laurate (12:0) LC/MS neg 0.85 Long chain myristate (14:0)GC/MS 0.70 fatty acid palmitate (16:0) LC/MS neg 0.72 palmitoleate(16:1n7) GC/MS 0.70 margarate (17:0) GC/MS 0.60 stearate (18:0) LC/MSneg 0.75 oleate (18:1n9) GC/MS 0.56 stearidonate (18:4n3) LC/MS neg 0.66eicosenoate (20:1n9 or 11) LC/MS neg 0.59 dihomo-linoleate (20:2n6)LC/MS neg 0.63 mead acid (20:3n9) LC/MS neg 0.74 adrenate (22:4n6) LC/MSneg 0.75 8-hydroxyoctanoate LC/MS neg 0.72 3-hydroxydecanoate LC/MS neg0.51 16-hydroxypalmitate LC/MS neg 0.70 13-HODE + 9-HODE LC/MS neg 0.50Fatty acid, 12,13-hydroxyoctadec-9(Z)-enoate LC/MS neg 0.54 dihydroxy9,10-hydroxyoctadec-12(Z)-enoic acid LC/MS neg 0.48 Fatty acid, adipateGC/MS 0.62 dicarboxylate 2-hydroxyglutarate GC/MS 0.83 pimelate(heptanedioate) GC/MS 0.61 suberate (octanedioate) LC/MS pos 0.69sebacate (decanedioate) LC/MS neg 0.64 azelate (nonanedioate) LC/MS neg0.72 dodecanedioate LC/MS neg 0.65 tetradecanedioate LC/MS neg 0.57hexadecanedioate LC/MS neg 0.54 octadecanedioate LC/MS neg 0.53undecanedioate LC/MS neg 0.66 Eicosanoid 12-HETE LC/MS neg 0.57 Fattyacid propionylcarnitine LC/MS pos 0.79 metabolism butyrylcarnitine LC/MSpos 0.64 (also BCAA metabolism) Fatty acid valerylcarnitine LC/MS pos0.56 metabolism 3-dehydrocarnitine* LC/MS pos 0.71 hexanoylcarnitineLC/MS pos 0.58 octanoylcarnitine LC/MS pos 0.69 choline LC/MS pos 0.79chiro-inositol GC/MS 0.66 pinitol GC/MS 0.61 Ketone 3-hydroxybutyrate(BHBA) GC/MS 0.66 bodies 1,2-propanediol GC/MS 0.831-linoleoylglycerophosphoethanolamine* LC/MS neg 0.711-arachidonoylglycerophosphoethanolamine* LC/MS neg 0.762-arachidonoylglycerophosphoethanolamine* LC/MS neg 0.781-stearoylglycerophosphoinositol LC/MS neg 0.661-linoleoylglycerophosphoinositol* LC/MS neg 0.591-arachidonoylglycerophosphoinositol* LC/MS neg 0.611-palmitoylplasmenylethanolamine* LC/MS neg 0.72 hypoxanthine GC/MS 8.55inosine LC/MS neg 8.36 adenosine LC/MS pos 5.63 adenosine5′-monophosphate (AMP) LC/MS pos 20.92 Purine guanosine 5′-monophosphate (5′-GMP) LC/MS pos 5.74 metabolism, guanine containingPurine urate LC/MS neg 0.84 metabolism, urate metabolism2′-deoxycytidine LC/MS pos 1.32 Pyrimidine uracil GC/MS 0.64 metabolism,pseudouridine LC/MS neg 0.89 uracil containing Nicotinate nicotinamideLC/MS pos 0.79 and nicotinamide metabolism catechol sulfate LC/MS neg0.77 Drug salicylate LC/MS neg 0.68 equol sulfate LC/MS neg 0.70 Sugar,sugar erythritol GC/MS 0.79 substitute, starch

Example 7 B. fragilis Treatment Corrects Levels of MIA-Induced SerumMetabolites

This examples shows B. fragilis-mediated improvement of intestinalbarrier integrity prevents alterations in serum metabolite levels.

4-ethylphenylsulfate (4EPS), indolepyruvate and several other serummetabolites are significantly altered by MIA treatment and restored tocontrol levels by B. fragilis treatment (FIG. 13A). MIA offspringdisplayed a striking, 46-fold increase in serum levels of4-ethylphenylsulfate (4EPS) which was dramatically reduced by B.fragilis treatment (FIG. 13A). Moreover, it was found that compared toconventionally colonized mice, germ-free mice display nearlyundetectable levels of serum 4EPS, indicating that serum 4EPS is derivedfrom, or critically modulated by, the commensal microbiota (FIG. 13B).4EPS has been suggested to be a uremic toxin, as is p-cresol(4-methylphenol), a related metabolite identified as a possible urinarybiomarker for human autism (Altieri et al., 2011; Persico and Napolioni,2013). MIA offspring also exhibited elevated levels of serum p-cresol,although the increase did not reach statistical significance (Table 4).The fact that 4EPS shares close structural similarity to the toxicsulfated form of p-cresol (4-methylphenylsulfate; 4 MPS) is intriguingas the two metabolites may exhibit functional overlap (FIG. 14A) andlink metabolite abnormalities seen in the MIA model to those observed inhuman ASD.

In addition to 4EPS, MIA offspring displayed significantly increasedlevels of serum indolepyruvate, a key molecule of the tryptophanmetabolism pathway, which was restored to control levels by B. fragilistreatment (FIG. 13A). Indolepyruvate is generated by tryptophancatabolism and, like 4EPS, indolepyruvate is believed to be produced bygut microbes (Smith and Macfarlane, 1997) (FIG. 14B). Moreover, theelevation in serum indolepyruvate observed in MIA offspring is analogousto the increase in another major tryptophan metabolite observed in humanautism, indolyl-3-acryloylglycine (IAG), which was suggested to be aurinary biomarker for ASD (Bull et al., 2003). Interestingly, IAG isinvolved in GI homeostasis and is produced by bacterial tryptophanmetabolism (Keszthelyi et al., 2009). It is notable that MIA offspringexhibited increased levels of serum serotonin (0.05<P<0.10), whichreflects an alteration in another pathway of tryptophan metabolism andis reminiscent of the hyperserotonemia endophenotype of autism (Mulderet al., 2004). Importantly, the commensal microbiota is known to impactserum levels of indole-containing tryptophan metabolites and serotonin(Wikoff et al., 2009). MIA also led to altered serum glycolate,imidazole propionate and N-acetylserine levels (FIG. 13A), which werecorrected by B. fragilis treatment.

This example demonstrates that specific metabolites are altered in MIAoffspring and normalized by B. fragilis treatment.

Example 8 A Serum Metabolite Induces ASD-Related Behaviors

MIA-dependent increases in the systemic bioavailability of specificmetabolites, and restoration by B. fragilis, suggest that thesemolecules play a causative role in ASD-related behaviors in MIAoffspring. This example examined whether experimentally increasing serum4EPS, the most dramatic of all metabolites affected by gut bacteria, issufficient to cause any ASD-related behavioral abnormalities in naïvemice.

4EPS was chemically synthesized by treatment of 4-ethylphenol withsulfur trioxide-pyridine complex, which, following ion exchange, yields4EPS potassium salt (FIGS. 15A-C) (Burlingham et al., 2003; Grimes,1959). Mice were intraperitoneally treated with 4EPS or saline vehicledaily, from 3 weeks of age (when increased gut permeability was detectedin MIA offspring, see FIG. 1A) to 6 weeks of age (when behavior testingbegan).

Remarkably, systemic administration of 4EPS to naïve wild-type mice wassufficient to induce anxiety-like behavior similar to that observed inMIA offspring (FIG. 13C). Relative to vehicle-treated controls, miceexposed to 4EPS traveled comparable distances in the open field butspent less time in the center arena (FIG. 13C). Notably, vehicle-treatedcontrols exhibited symptoms of anxiety-like behavior compared tountreated saline offspring (center entries: 14.5±1.1 versus 23.7±1.4;center duration (s): 29.4±5.4 versus 46.4±4.2; distance (m): 35.6±1.8versus 37.6±1.0, comparing vehicle-treated mice (Veh.) in FIG. 13C tosaline offspring (S) in FIG. 10A). This reflects the well-known effectof chronic stress (daily injection) on raising anxiety levels in miceand humans (Bailey and Crawley, 2009; Bourn et al., 2007). Also, in thePPI test, 4EPS-treated mice exhibited increased intensity of startle inresponse to the unconditioned primary stimulus, but no significantalterations in PPI (FIG. 13D), representing anxiety-associatedpotentiation of the startle reflex (Bourn et al., 2007). Also, there wasno difference in weight between 4EPS− and control-treated mice, andthus, no confounding effect of body mass on measured startle intensity.Conversely, there were no significant differences between 4EPS-treatedversus saline-treated mice in marble burying or USV behavior (FIGS. 15Dand 15E), suggesting that elevating serum 4EPS levels specificallypromoted anxiety-like behavior.

Example 9 Treatment of Autism Spectrum Disorder (ASD)

This example illustrates the treatment of a patient suffering from ASD.

A patient is identified as being suffering from ASD. The blood level of4EPS in the subject is determined. A composition with B. fragilis isadministered to the patient via oral administration. The administrationof B. fragilis is expected to alter the blood level of 4EPS andcomposition of gut microbiota in the patient. It is also expected thatthe bacterial administration will relieve one or more symptoms of ASD,such as improve behavioral performance, in the patient.

Example 10 Treatment of Autism Spectrum Disorder (ASD)

This example illustrates the treatment of a patient suffering from ASD.

A patient is identified as being suffering from ASD. The urine level of4-methylphenysulfate in the subject is determined. A composition with B.fragilis is administered to the patient via oral administration. Theadministration of B. fragilis is expected to alter the urine level of4-methylphenysulfate and the composition of gut microbiota in thepatient. It is also expect that the bacterial administration willrelieve one or more symptoms of ASD, such as improve behavioralperformance, in the patient.

The foregoing description and examples detail certain preferredembodiments of the invention and describes the best mode contemplated bythe inventors. It will be appreciated, however, that no matter howdetailed the foregoing may appear in text, the invention may bepracticed in many ways and the invention should be construed inaccordance with the appended claims and any equivalents thereof.Although the present application has been described in detail above, itwill be understood by one of ordinary skill in the art that variousmodifications can be made without departing from the spirit of theinvention.

In this application, the use of the singular can include the pluralunless specifically stated otherwise or unless, as will be understood byone of skill in the art in light of the present disclosure, the singularis the only functional embodiment. Thus, for example, “a” can mean morethan one, and “one embodiment” can mean that the description applies tomultiple embodiments. Additionally, in this application, “and/or”denotes that both the inclusive meaning of “and” and, alternatively, theexclusive meaning of “or” applies to the list. Thus, the listing shouldbe read to include all possible combinations of the items of the listand to also include each item, exclusively, from the other items. Theaddition of this term is not meant to denote any particular meaning tothe use of the terms “and” or “or” alone. The meaning of such terms willbe evident to one of skill in the art upon reading the particulardisclosure.

All references cited herein including, but not limited to, published andunpublished patent applications, patents, text books, literaturereferences, and the like, to the extent that they are not already, arehereby incorporated by reference in their entirety. To the extent thatone or more of the incorporated literature and similar materials differfrom or contradict the disclosure contained in the specification,including but not limited to defined terms, term usage, describedtechniques, or the like, the specification is intended to supersedeand/or take precedence over any such contradictory material.

The term “comprising” as used herein is synonymous with “including,”“containing,” or “characterized by,” and is inclusive or open-ended anddoes not exclude additional, unrecited elements or method steps.

1. A method for improving behavioral performance in a subject,comprising: determining the blood level of an autism spectrum disorder(ASD)-related metabolite in a subject in need of treatment; andadjusting the blood level of the ASD-related metabolite in the subjectuntil an improvement in the behavioral performance in the subject isobserved.
 2. The method of claim 1, wherein the subject suffers fromanxiety, autism spectrum disorder (ASD), or a pathological conditionwith one or more of the symptoms of ASD.
 3. The method of claim 2,wherein the subject suffers from ASD.
 4. The method of claim 1, whereinadjusting the blood level of the ASD-related metabolite comprisesadjusting the composition of gut microbiota in the subject.
 5. Themethod of claim 4, wherein adjusting the composition of gut microbiotaof the subject comprises fecal transplantation.
 6. The method of claim4, wherein adjusting the composition of gut microbiota of the subjectcomprises administering the subject a composition comprising Bacteroidesbacteria.
 7. The method of claim 6, wherein the Bacteroides bacteria isB. fragilis, B. thetaiotaomicron, B. vulgatus, or a mixture thereof. 8.The method of claim 6, wherein the composition is a probioticcomposition, a neutraceutical, a pharmaceutical composition, or amixture thereof.
 9. The method of claim 4, wherein adjusting thecomposition of gut microbiota of the subject comprises reducing thelevel of Clostridia bacteria in the subject.
 10. The method of claim 9,wherein the Clostridia bacteria is Lachnospiraceae.
 11. The method ofclaim 4, wherein adjusting the composition of gut microbiota of thesubject comprises increasing the level of Ruminococcaceae,Erysipelotrichaceae, and/or Alcaligenaceae bacteria in the subject. 12.The method of claim 1, wherein the ASD-related metabolite is one of themetabolites listed in Table
 1. 13. The method of claim 12, wherein theASD-related metabolite is a metabolite involved in tryptophanmetabolism, a metabolite involved in fatty acid metabolism, a metaboliteinvolved in purine metabolism, glycolate, imidazole propionate, orN-acetylserine.
 14. The method of claim 13, wherein the metaboliteinvolved in tryptophan metabolism is 4-ethylphenylsulfate,indolepyruvate, indolyl-3-acryloylglycine, or serotonin.
 15. The methodof claim 1, wherein the ASD-related metabolite is 4-ethylphenylsulfate,indolepyruvate, glycolate, or imidazole proprionate.
 16. The method ofclaim 1, wherein adjusting the blood level of the ASD-related metabolitein the subject comprises administering to the subject an antibodyagainst the ASD-related metabolite, an antibody against an intermediatefor the in vivo synthesis of the ASD-related metabolite, or an antibodyagainst a substrate for the in vivo synthesis of the ASD-relatedmetabolite.
 17. The method of claim 16, wherein the ASD-relatedmetabolite is 4-ethylphenylsulfate or indolepyruvate.
 18. The method ofclaim 16, wherein adjusting the blood level of the ASD-relatedmetabolite in the subject comprises inhibiting an enzyme involved in thein vivo synthesis of the ASD-related metabolite.
 19. The method of claim1, wherein adjusting the blood level of the ASD-related metaboliteameliorates gastrointestinal (GI) distress of the subject.
 20. Themethod of claim 19, wherein the GI distress comprises abdominal cramps,chronic diarrhea, constipation, intestinal permeability, or acombination thereof.
 21. The method of claim 1, wherein adjusting theblood level of the ASD-related metabolite reduces intestinalpermeability of the subject.
 22. The method of claim 1, furthercomprising determining the reference level of the metabolite innon-autistic subjects.
 23. The method of claim 1, further comprisingdetermining the behavioral performance of the subject prior to and afteradjusting the blood level of the ASD-related metabolite in the subject.24. The method of claim 23, wherein determining the behavioralperformance of the subject comprises using Autism Behavior Checklist(ABC), Autism diagnostic Interview-Revised (ADI-R), childhood autismRating Scale (CARS), and/or Pre-Linguistic Autism Diagnostic ObservationSchedule (PL-ADOS).
 25. A method for improving behavioral performance ina subject, comprising: determining the urine level of an autism spectrumdisorder (ASD)-related metabolite in a subject in need of treatment; andadjusting the urine level of the ASD-related metabolite in the subjectuntil an improvement in behavioral performance in the subject isobserved.
 26. The method of claim 25, wherein the ASD-related metaboliteis 4-methylphenyl, 4-methylphenylsulfate or indolyl-3-acryloylglycine.27. The method of claim 25, wherein adjusting the urine level of theASD-related metabolite comprises adjusting the composition of gutmicrobiota in the subject.
 28. The method of claim 27, wherein adjustingthe composition of gut microbiota of the subject comprises administeringthe subject a composition comprising Bacteroides bacteria.
 29. A methodfor assessing the susceptibility of a subject suffering from autismspectrum disorder (ASD) to probiotic treatment, comprising: determiningthe blood level of a B. fragilis-responsive metabolite in the subject;and comparing the blood level of the B. fragilis-responsive metabolitein the subject to a reference level of the metabolite in subjectssuffering from ASD and one or more gastrointestinal disorders, whereinsubstantial identity between the blood level of the metabolites in thesubject and the reference level indicates that the subject issusceptible to the probiotic treatment.
 30. The method of claim 29,comprising adjusting the composition of gut microbiota of the subject.31. The method of claim 30, wherein adjusting the composition of gutmicrobiota of the subject comprises administering the subject acomposition comprising Bacteroides bacteria.
 32. The method of claim 31,wherein the Bacteroides bacteria is B. fragilis, B. thetaiotaomicron, B.vulgatus, or a mixture thereof.
 33. The method of claim 30, whereinadjusting the composition of gut microbiota of the subject comprisesfecal transplantation.
 34. The method of claim 29, wherein the B.fragilis-responsive metabolite is one of the metabolites listed in Table2.
 35. A method for relieving gastrointestinal (GI) distress of asubject suffering from autism spectrum disorder (ASD), comprisingreducing intestinal permeability in the subject.
 36. The method of claim35, wherein the GI distress comprises abdominal cramps, chronicdiarrhea, constipation, intestinal permeability, or a combinationthereof.
 37. The method of claim 35, wherein reducing intestinalpermeability comprises adjusting the composition of gut microbiota inthe subject.
 38. A method for diagnosing autism spectrum disorder (ASD)in a subject, comprising: determining the level of a cytokine in gut andthe blood level of one or more ASD-related metabolites in the subject;and detecting whether or not there is an alteration in the level of thecytokine in gut and the blood level of at least one or more of theASD-related metabolites in the subject as compared to a reference levelof the cytokine and the metabolite in non-autistic subjects, whereby analteration in the amount of the cytokine in gut and the blood level ofat least one of the one or more metabolites indicates that the subjectsuffers from ASD.
 39. The method of claim 38, wherein the cytokine isinterleukin-6 (IL-6).
 40. A method for diagnosing autism spectrumdisorder (ASD) in a subject, comprising: determining the blood level oftwo or more ASD-related metabolites in the subject; and detectingwhether or not there is an alteration in the blood level of the two ormore ASD-related metabolites in the subject as compared to a referencelevel of the metabolites in non-autistic subjects, whereby an alterationin the blood level of at least two of the two or more ASD-relatedmetabolites indicates that the subject suffers from ASD.
 41. The methodof claim 38, wherein the one or more of the ASD-related metabolites areselected from the metabolites listed in Table
 1. 42. The method of claim38, comprising altering the level of one or more ASD-related metabolitesin the subject to improve behavioral performance in the subject if it isindicated that the subject suffers from ASD.
 43. The method of claim 40,wherein the one or more of the ASD-related metabolites are selected fromthe metabolites listed in Table
 1. 44. The method of claim 40,comprising altering the level of one or more ASD-related metabolites inthe subject to improve behavioral performance in the subject if it isindicated that the subject suffers from ASD.